Software Engineer - Machine Learning (Technical Leadership)

לפני 6 שעות

Software Engineer - Machine Learning (Technical Leadership)

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

Meta is reimagining shopping on our company, Instagram, and Muse. The vision is to make every piece of media shoppable. Behind that vision is our Product Recognition and Intelligence stack. It is the tech that looks at any photo, video, and text, and knows exactly which products are in it and how they relate to other products. We are building it to work at Meta's scale. Over 3 billion distinct users every day. Billions of items power a multibillion-dollar ad business.
We are hiring a senior staff Machine Learning Engineer to lead this journey. You will tackle the hardest ML systems challenges in training, serving, and evaluation. You will set the architecture and standards that raise the bar across organizations. You will ship state-of-the-art models to production where they touch billions.
If you want to have an impact at a global scale and love building tech that actually ships, come build with us.
Software Engineer - Machine Learning (Technical Leadership) Responsibilities
Identify and solve the most complex machine learning systems problems across the organization, including model training efficiency, large-scale inference optimisation, and cross-system ML pipeline reliability
Define and own the technical architecture for critical ML infrastructure components, ensuring designs are extensible, maintainable, and capable of supporting the next generation of model development at Meta's scale
Establish engineering standards and invariants for ML systems that prevent entire categories of reliability, correctness, and performance issues across multiple teams
Drive cross-organizational technical strategy by assessing emerging ML technologies, evaluating trade-offs between competing approaches, and influencing roadmap decisions with leadership and cross-functional partners
Lead the design and delivery of org-wide ML platform initiatives, coordinating across engineering teams, research, product, and data science to align on priorities and drive execution through ambiguity
Develop new metrics and data-driven frameworks for evaluating ML system health, model quality, and infrastructure efficiency, and connecting them to organization-level goals
Mentor and coach engineers across the organization on ML system design, debugging complex models and infrastructure failures, and developing scalable solutions to recurring technical challenges
Collaborate with privacy, security, and compliance teams to design ML systems that uphold user safety, meet regulatory requirements, and set the standard for responsible AI practices within the business domain
Identify and eliminate engineering bottlenecks through improved tooling, automation, and process improvements that make ML development faster and more reliable across the organization
Contribute to recruiting efforts by building relationships with candidates who bring critical ML systems expertise, and serve as a technical reference point for evaluating engineering talent at the most senior levels.

Requirements:
Minimum Qualifications
12+ years of experience designing, building, and operating large-scale machine learning systems in production environments
Experience architecting ML infrastructure components such as distributed training pipelines, model serving systems, feature stores, or ML evaluation frameworks at a significant scale
Experience in identifying and resolving systemic performance, reliability, or correctness issues that span multiple ML systems or abstraction layers
Experience influencing technical direction across multiple engineering teams through written proposals, design reviews, and cross-functional stakeholder alignment
Experience defining engineering standards, architectural patterns, or platform capabilities that have been adopted broadly across an organization
Preferred Qualifications
Experience in building large-scale object recognition models.

This position is open to all candidates.

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8897304

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לפני 6 שעות

Machine Learning Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

Meta is seeking a Machine Learning Engineer to design, build, and deploy machine learning systems across a broad range of product areas including ranking, recommendations, natural language understanding, computer vision, and integrity. In this role, you will own the full ML development lifecycle - from data pipeline construction and feature engineering through model training, evaluation, and production deployment - contributing directly to systems that serve billions of users at global scale.
Machine Learning Engineer Responsibilities
Design and implement end-to-end machine learning pipelines spanning data ingestion, feature engineering, model training, offline evaluation, and production serving
Develop and optimize models for large-scale applications such as ranking, recommendations, classification, and natural language understanding
Instrument model performance with robust monitoring, alerting, and dashboards to detect regressions and maintain production reliability
Drive A/B experiment design and analysis to validate model improvements, articulate trade-offs, and make data-informed launch decisions
Architect scalable ML infrastructure and reusable components that accelerate development velocity across the team
Identify and resolve complex model quality issues through systematic debugging, root cause analysis, and defensive engineering practices
Collaborate with product managers, data scientists, and software engineers to translate product requirements into ML problem formulations and technical roadmaps
Define and evolve ML platform standards, coding best practices, and testing frameworks to improve engineering quality across the organization
Mentor other engineers on ML methodology, system design, and engineering craft, and contribute to recruiting by conducting technical interviews.

Requirements:
Minimum Qualifications
6+ years of experience developing and deploying machine learning models in production environments
Experience with large-scale ML frameworks such as PyTorch, TensorFlow, or JAX, and proficiency in Python for model development and data processing
Experience designing and optimizing ML systems for ranking, recommendations, classification, or natural language understanding at scale
Experience with feature engineering, offline and online model evaluation, and A/B experimentation methodologies
Experience building reliable, monitored ML pipelines with observability tooling including dashboards, alerting, and logging
Preferred Qualifications
Familiarity with ML platform infrastructure including feature stores, model registries, and automated retraining pipelines
Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
Experience with distributed training frameworks and large-scale model optimization techniques such as quantization, distillation, or pruning
Track record of driving cross-functional ML projects from problem definition through production impact, including influencing technical direction across teams
Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
Experience applying ML to integrity, personalization, or real-time inference systems with strict latency requirements.

This position is open to all candidates.

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8897418

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לפני 6 שעות

Software Engineer, ML (Technical Leadership)

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

The financial risk management (FRM) machine learning principal will be the most senior machine learning engineer and strategist for financial risk at Meta. The principal will enable the risk organization to deliver significant lift over current long range objectives for friction and leakage through the generation of new Machine Learning opportunities for the organization and support of successful delivery of the risk management ML architecture. This person will partner closely with the FRM engineering leader (Director level) and be part of Metas risk management leadership circle.
Software Engineer, ML (Technical Leadership) Responsibilities
Address core business and technical machine learning opportunities: elevate the existing portfolio of machine learning solutions to be state-of-the-art for minimizing Metas financial losses (due to leakage, good revenues loss and friction). Following are a few examples of technical and business problems we aim to address. - Provide a solution for optimizing the risk machine learning model ensemble (covering the entire end-to-end advertiser funnel including detection, decisioning, enforcement and remediation) through optimization of the current model portfolio and individual models. - Minimize the impact of the prolonged financial fraud feedback loop. - Improve models measurement and performance. - Optimize data/label strategy. - Optimize balance between specific targeted model strategy and broad umbrella model strategy to optimize for short and long term benefits
Lead Research and Introduction of Advanced Technologies: - Collaborate with Financial Integrity's senior ML Engineers to lead the research and introduction of deep learning and Large Language Model (LLM) technologies. - Remain current on industry-wide advancements in ML and introduce relevant advancements in Financial Risk Management
Collaborate on Next-Generation ML Architecture: - Work closely with financial harms principals and risk management tech leads to deliver the next-generation ML architecture for Meta's risk management system. - Collaborate with Principal ML engineers from across the company to adopt best industry and Meta practices within the FRM team. - Resolve or mitigate design dilemmas, balancing business and technical trade-offs. - Identify and initiate opportunities for collaboration and impact with other organizations at Meta
Identify and Initiate New Business Opportunities: - Collaborate with Meta FinTech, Central Integrity and Core Ads Growth partnerships to identify and initiate new business opportunities based on third-party capabilities. - Conduct proof of concept for different opportunities and initiate integrations to enhance business performance
Grow Other Senior ML Engineers - Actively invest in the growth of other senior ML engineers through goal-driven formal and informal mentorship. Provide regular feedback to other engineers regarding their technical work.

Requirements:
Minimum Qualifications
Extensive experience in supporting and evolving a portfolio of ML models that deliver on critical business goals
Preferred Qualifications
Experience working with ML models in financial risk or similar financial contexts.

This position is open to all candidates.

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8897349

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06/10/2026

Machine Learning Hardware Architect, Hardware, Software Co-Design, Cloud

חברה חסויה

Location: Tel Aviv-Yafo and Haifa

Job Type: Full Time

Required Machine Learning Hardware Architect, Hardware, Software Co-Design, Cloud
About the job
In this role, youll work to shape the future of AI/ML hardware acceleration. You will have an opportunity to drive cutting-edge TPU (Tensor Processing Unit) technology that powers our most demanding AI/ML applications. Youll be part of a team that pushes boundaries, developing custom silicon solutions that power the future of our TPU. You'll contribute to the innovation behind products loved by millions worldwide, and leverage your design and verification expertise to verify complex digital designs, with a specific focus on TPU architecture and its integration within AI/ML-driven systems.
As a Machine Learning Hardware Architect within the Co-design team, you will serve as a technical lead bridging model architecture innovation and next-generation hardware design. Operating at the highest levels of AI research and engineering, you will define the goal and architectural roadmap for our future machine learning serving and training capabilities. You will guide the integration of ML research such as massive-scale foundation models with advanced silicon architectures to create industry-leading, high-performance, and power-efficient accelerators.
Responsibilities:
Define and drive the technical roadmap and architecture for the hardware/software stack to ensure exceptional performance for ML models. Act as the technical liaison across research, software, and hardware teams, steering model architecture innovation to maximize scaling, quality, and hardware efficiency.
Architect next-generation configurable simulation frameworks and performance models, setting the organizational standard for evaluating complex microarchitectural decisions. Drive high-stakes choices regarding Power, Performance, Area (PPA) and buildability for future chip and system architectures, expertly balancing long-term technological trends with strict product delivery timelines.
Guide system-level performance analysis across highly distributed ML systems, innovating new methodologies to optimize and balance compute, memory bandwidth, and inter-chip network requirements. Their leadership will directly shape the future of high-performance AI infrastructure and hardware-software co-design.
Manage cross-functional partnerships across hardware, compiler development and ML teams.

Requirements:
Minimum qualifications:
Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience.
12 years of experience in computer architecture, chip architecture, or hardware-software co-design.
Experience architecting and developing software systems in C++ or Python for performance modeling, simulation, or system analysis.
Preferred qualifications:
Masters degree or PhD in Electrical Engineering, Computer Engineering, or Computer Science with an emphasis on computer architecture.
Experience as a lead architect managing multi-generational hardware solutions or performance optimizations for massive-scale ML training and inference.
Experience in semiconductor technologies, industry trends, and the future trajectory of process, memory, interconnects, and packaging.
Experience with deep learning frameworks (e.g., TensorFlow, PyTorch) and deep understanding of their underlying execution models.

This position is open to all candidates.

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לפני 6 שעות

Software Engineer, Systems

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

we are seeking a Software Engineer to design, build, and scale the foundational systems infrastructure that powers products used by billions of people worldwide. In this role, you will work across the systems stack - spanning distributed systems, storage, networking, runtime environments, and platform services - to deliver reliable, high-performance infrastructure that enables product teams to move quickly and safely at scale. You will own technical design and execution across complex, cross-cutting systems projects, partnering closely with engineers across the organization to drive engineering excellence and long-term platform health.
Software Engineer, Systems Responsibilities
Design and implement scalable, reliable systems infrastructure components spanning distributed computing, storage, networking, or runtime environments
Own end-to-end technical design for systems-level projects, evaluating architectural trade-offs and driving decisions that balance performance, reliability, and maintainability
Instrument systems with telemetry, dashboards, and alerting to establish visibility into performance bottlenecks, reliability regressions, and failure modes
Lead incident response and root cause analysis for production systems issues, authoring retrospectives and driving follow-up improvements to prevent recurrence
Define and enforce service level objectives for owned systems, building debugging runbooks and mitigation playbooks to reduce mean time to resolution
Collaborate with cross-functional partners across product engineering, infrastructure, and security to ensure systems designs meet privacy, security, and integrity requirements
Drive engineering efficiency by identifying development bottlenecks, building internal tooling and automation, and completing migrations that eliminate legacy technical debt
Mentor other engineers on systems design principles, coding standards, and operational best practices, and contribute to recruiting and technical program efforts
Analyze performance profiles using instrumentation and profiling tools to identify hotspots and drive targeted optimizations across the systems stack
Communicate technical decisions, trade-offs, and project status clearly to stakeholders across engineering levels and cross-functional roles.

Requirements:
Minimum Qualifications
6+ years of experience in systems software engineering, including work on distributed systems, storage systems, networking infrastructure, or operating system-level components
Experience designing and implementing large-scale, production systems with well-defined reliability, performance, and operational requirements
Experience debugging complex, non-reproducible systems issues using advanced tooling such as profilers, static analyzers, tracing frameworks, or custom instrumentation
Experience establishing observability for production systems through metrics, dashboards, alerting, and service level objectives
Experience driving cross-team technical projects from design through production, including dependency coordination, staged rollout planning, and post-launch monitoring
Preferred Qualifications
Familiarity with resiliency testing methodologies such as overload testing, chaos engineering, or fault injection for distributed systems
Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
Experience with systems programming languages such as C, C++, Rust, or Go in a production environment
Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
Experience contributing to platform or infrastructure projects that are consumed by multiple product or engineering teams
Track record of improving developer productivity through tooling, automation, or codebase modernization efforts at an organizational scale.

This position is open to all candidates.

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8897343

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לפני 5 שעות

Software Engineer, Systems

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

we are seeking a Staff Systems Software Engineer to design and build the foundational infrastructure that powers products used by billions of people worldwide. In this role, you will architect and implement large-scale distributed systems, low-level platform components, and high-performance services that underpin our company's core product stack. You will drive technical strategy across system reliability, performance, and scalability, partnering closely with product, infrastructure, and data engineering teams to deliver systems that operate at global scale with high availability and efficiency.
Software Engineer, Systems Responsibilities
Architect and implement large-scale distributed systems and platform services that support high-throughput, low-latency workloads across our company's product infrastructure
Lead the technical design of systems components including storage layers, compute pipelines, networking abstractions, and service orchestration frameworks
Identify and resolve systemic performance bottlenecks through instrumentation, profiling, and targeted optimization across the full systems stack
Define and enforce service level objectives for owned systems, building dashboards, alerting pipelines, and runbooks to reduce mean time to mitigation during incidents
Drive reliability improvements by reducing failure surface, designing resilient rollout strategies, and leading regular resiliency and overload testing exercises
Collaborate with cross-functional partners across product engineering, infrastructure, and data science to align system architecture with evolving product and business requirements
Establish and evolve coding standards, architectural patterns, and engineering best practices for systems development across the broader organization
Leverage AI-assisted development workflows to accelerate design iteration, code generation, and systems analysis, applying sound judgment on when to rely on AI versus deep systems expertise
Mentor other engineers on systems design principles, debugging methodologies, and production operations, and contribute to onboarding programs for new team members
Lead incident retrospectives, identify root causes of complex production failures, and drive implementation of systemic improvements to prevent recurrence.

דרישות:
Minimum Qualifications
8+ years of experience designing and implementing large-scale distributed systems, platform infrastructure, or systems software in production environments
Experience leading major technical initiatives end-to-end, including architecture design, cross-team coordination, staged rollout, and post-launch reliability ownership
Experience debugging complex, non-reproducible systems issues including concurrency bugs, memory management failures, and distributed consistency problems
Experience defining service level objectives, building observability infrastructure, and driving reliability improvements across production systems
Experience communicating technical architecture decisions and trade-offs in writing to both engineering and non-engineering stakeholders
Preferred Qualifications
Experience with systems programming languages such as C, C++, or Rust in the context of high-performance or low-latency infrastructure
Experience building or improving developer tooling, automation frameworks, or internal platforms that measurably improve engineering efficiency across teams
Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
Experience designing or contributing to storage systems, compute scheduling frameworks, or inter-service communication protocols a המשרה מיועדת לנשים ולגברים כאחד.

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8897437

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14/10/2026

AI Staff Software Engineer, ML Platform

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

This is a Principal AI Software Engineer role at the heart of our companys AI Engineering group-where algorithms, infrastructure, and products intersect. Youll lead the evolution and scaling of our companys AI architecture, ensuring reliability, efficiency, and impact across global clinical workflows. The role combines technical depth with cross-functional influence, strengthening how our AI systems are built, integrated, and delivered to drive ongoing impact for patients and care teams.
Responsibilities
Lead cross-domain engineering initiatives connecting AI algorithms (CV, NLP, and deep-learning systems), software, and data systems-from design to delivery.
Stay hands-on, contributing to AI-serving (training and inference), integration, and orchestration components while setting high technical standards.
Partner with Algo teams to connect algorithmic innovation with strong system design, ensuring smooth delivery across Product and Engineering.
Guide architectural evolution, ensuring efficiency, consistency, and maintainability across AI workflows.
Communicate direction and priorities clearly, aligning teams around technical goals.
Mentor engineers and promote technical excellence, sound design, and shared best practices.
Foster collaboration and shared ownership, helping maintain a culture that values clarity, curiosity, and technical excellence.
Uphold quality and reliability-including clean code, testing, and CI/CD discipline-while evaluating and adopting new tools that enhance performance and long-term scalability.

Requirements:
Masters or Ph.D. in Computer Science, Engineering, or a related technical field.
10+ years of software engineering experience with proven architectural depth and a strong hands-on approach.
Proven ability to drive technical direction, make architecture decisions, and align diverse stakeholders.
Strong understanding of AI/ML systems, including deep learning, computer vision, and NLP-able to design and support systems that integrate these models effectively.
Experience designing and building robust software architectures with a focus on scalability, reliability, and maintainability.
Proficiency in Python and modern software engineering practices (clean code, testing, CI/CD, observability, and performance optimization), along with experience using deep learning frameworks such as PyTorch and Tensorflow
Familiarity with cloud environments and MLOps practices, including containerization, orchestration, and model-serving frameworks.
Excellent collaboration and communication skills, with a mindset that combines engineering rigor, curiosity, and purpose.

This position is open to all candidates.

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8857328

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04/10/2026

Senior ML Research Engineer 25769

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

Join our companys AI research group, a cross-functional team of ML engineers, researchers and security experts building the next generation of AI-powered security capabilities. Our mission is to leverage large language models to understand code, configuration, and human language at scale, and to turn this understanding into security AI capabilities which will drive our company AI future security solutions.
We foster a hands-on, research-driven culture where youll work with large-scale data, modern ML infrastructure, and a global product footprint that impacts over 100,000 organizations worldwide.
Key Responsibilities
Your Impact & Responsibilities
As a Senior ML Research Engineer, you will be responsible for the end-to-end lifecycle of large language models: from data definition and curation, through training and evaluation, to providing robust models that can be consumed by product and platform teams.
Own training and fine-tuning of LLMs / seq2seq models: Design and execute training pipelines for transformer-based models (encoder-decoder, decoder-only, retrievalaugmented, etc.), and fine-tune open-source LLMs on our company-specific data (security content, logs, incidents, customer interactions).
Apply advanced LLM training techniques such as instruction tuning, preference / contrastive learning, LoRA / PEFT, continual pre-training, and domain adaptation where appropriate.
Work deeply with data: define data strategies with product, research and domain experts; build and maintain data pipelines for collecting, cleaning, de-duplicating and labeling large-scale text, code and semi-structured data; and design synthetic data generation and augmentation pipelines.
Build robust evaluation and experimentation frameworks: define offline metrics for LLM quality (task-specific accuracy, calibration, hallucination rate, safety, latency and cost); implement automated evaluation suites (benchmarks, regression tests, redteaming scenarios); and track model performance over time.
Scale training and inference: use distributed training frameworks (e.g. DeepSpeed, FSDP, tensor/pipeline parallelism) to efficiently train models on multi-GPU / multi-node clusters, and optimize inference performance and cost with techniques such as quantization, distillation and caching.
Collaborate closely with security researchers and data engineers to turn domain knowledge and threat intelligence into high-value training and evaluation data, and to expose your models through well-defined interfaces to downstream product and platform teams.

Requirements:
What You Bring
5+ years of hands-on work in machine learning / deep learning, including 3+ years focused on NLP / language models.
Proven track record of training and fine-tuning transformer-based models (BERT-style, encoder-decoder, or LLMs), not just consuming hosted APIs.
Strong programming skills in Python and at least one major deep learning framework (PyTorch preferred; TensorFlow).
Solid understanding of transformer architectures, attention mechanisms, tokenization, positional encodings, and modern training techniques.
Experience building data pipelines and tools for large-scale text / log / code processing (e.g. Spark, Beam, Dask, or equivalent frameworks).
Practical experience with ML infrastructure, such as experiment tracking (Weights & Biases, MLflow or similar), job orchestration (Airflow, Argo, Kubeflow, SageMaker, etc.), and distributed training on multi-GPU systems.
Strong software engineering practices: version control, code review, testing, CI/CD, and documentation.
Ability to own research and engineering projects end-to-end: from idea, through prototype and controlled experiments, to models ready for integration by product and platform teams.
Good communication skills and the ability to work closely with non-ML stakeholders (security experts, product managers, engineers).

This position is open to all candidates.

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8840766

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25/10/2026

Senior Machine Learning Engineer I - GenAI Applications Teams

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

Required Senior Machine Learning Engineer I - GenAI Applications Teams
26946 ID
About the team:
This opening is for the GenAI Applications Teams within the Data & AI Marketplace department.
The GenAI Applications teams are responsible for designing and delivering agentic, ML-powered solutions for some of our most impactful products, including booking search experiences, trip planning, and customer service. The teams build AI-driven applications and conversational agents, such as chatbots and intelligent assistants that significantly enhance the end-to-end customer experience.
Role Description:
As a Senior Machine Learning Engineer, you will work closely with top notch engineers and data scientists to design, develop, evaluate and deploy Gen AI-powered solutions for scalable, customer-facing applications. Your work will focus on building and applying state-of-the-art agentic capabilities to drive business impact and improve efficiency.
Key Job Responsibilities and Duties:
Design, develop, and deploy high-quality, performant, and efficient Generative AI-powered solutions and agentic systems into production environments.
Evaluate and define optimal architectural solutions by considering emerging technologies, business needs, and technical requirements for latency, throughput, and scale.
Own services end-to-end, including implementing robust monitoring and maintenance strategies to ensure application and ML health, quality, and performance.
Write and maintain clean, scalable, and well-tested production code, ensuring reproducibility and seamless integration via CI/CD pipelines.
Pioneer and promote best practices and the adoption of cutting-edge technology in GenAI application development.
Collaborate effectively with Product Managers, Data Scientists, and Analysts to understand business requirements and translate them into technical ML and agentic solutions.
Provide technical guidance and mentorship to other engineers, contributing to the team's overall technical development.

Requirements:
Bachelors or masters degree in Computer Science, Engineering, Statistics, or a related field.
Minimum of 6 years of experience as a Machine Learning Engineer or a similar role, with a consistent record of successfully delivering ML solutions to production.
Experience of working on products that impact a large customer base.
Demonstrable experience and capabilities with Generative AI applications, including Large Language Models (LLMs), Agentic Systems, and MCP in production environments. Experience deploying large-scale language models (e.g., GPT, BERT, or similar architectures) - an advantage.
Deep understanding of core machine learning algorithms, statistical models, evaluation methods, and data structures.
Experience in designing, building, and deploying models using cloud frameworks (e.g., AWS Sagemaker) and standard ML libraries (e.g., TensorFlow, PyTorch, or scikit-learn).
Strong programming proficiency in languages such as Python and Java.
Strong coding practices, including writing and reviewing production-quality, maintainable, and well-tested code, with the ability to effectively leverage modern AI coding assistants while maintaining high standards for correctness, readability, and system design.
Experience with big data processing frameworks (e.g., Pyspark, Apache Flink, Snowflake) and demonstrable experience with relational/NoSQL database systems (e.g., MySQL, Cassandra, DynamoDB).
Excellent English communication and presentation skills, both written and verbal.
Proficiency in data manipulation, analysis, and visualization using tools like NumPy, pandas, and matplotlib - an advantage.
Experience with experimental design, A/B testing, and evaluation metrics for ML models - an advantage.

This position is open to all candidates.

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8871118

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1 ימים

backend engineer - ml platform

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

we're looking for a backend engineer to help build and scale the Machine Learning platform that powers how the company uses ai across the business. you'll be part of the ml platform team, designing the infrastructure that lets our data scientists move faster, ship smarter, and operate with confidence in production.
we believe three things matter for every role at the company: drive to push through challenges, efficiency that keeps standards high while moving fast, and adaptability that lets you pivot with data and ai insights. these aren't buzzwords, they're how we actually work. our ai-first approach isn't just a tagline either. we're building the future of insurance with ai at the center, and we need people who are genuinely excited to learn and grow alongside these tools.
in this role you'll:
design and build the foundational ml platform and ai agents to accelerate data science model delivery across all business units
architect cloud-native microservices running on kubernetes, using infrastructure-as-code to automate model deployment and management
own the end-to-end ml lifecycle, covering training, testing, deployment, and Real-Time monitoring
evaluate and choose the right tools and technologies based on workload demands and performance requirements
collaborate with engineering, data science, and product teams to keep ml projects aligned with business goals
identify and fix reliability, scalability, and performance gaps before they become problems.

Requirements:
what you'll need
3+ years of software engineering experience, with a strong record of delivering high-scale, production-grade systems
strong proficiency in Python
hands-on experience with relational and nosql databases, and at least one major cloud platform (aws, azure, or gcp)
experience with training, testing, deploying, and monitoring Real-Time or near Real-Time ml models in production
fluent with ai-powered development tools like cursor and claude code, and genuinely curious about what's next in genai, llms, and ai agents
familiarity with ai concepts like rag, embeddings, mixture-of-experts, prompt crafting, and llm context engineering - an advantage
sharp problem-solving instincts and the ability to move fast without cutting corners
bachelor's or master's degree in Computer Science, engineering, statistics, or a related field
ready to work in an office environment most days of the week

This position is open to all candidates.

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8895307

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לפני 3 שעות

Data Science Team Lead

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

As the Data Science Team Lead, you will lead a talented team of data scientists and ML engineers building the infrastructure, systems, and workflows for designing, training, evaluating, and deploying machine learning models that protect millions of users worldwide from fraud and account compromise.

This role combines hands-on technical leadership with people management and strategic ownership. You will drive innovation across real-time model serving, customer-specific model tuning, offline AI evaluations, and scalable ML systems in a production-grade SaaS environment.

If you are passionate about applied machine learning, fraud detection, and building intelligent systems at scale - we want you on our team.

What We Look for in Candidates:
Lead and mentor a team of Data Scientists focused on fraud detection and response capabilities.
Build ML infrastructure focused on design, train, evaluate, and optimize machine learning models for real-time fraud prevention and risk assessment.
Own the lifecycle of ML models in production, including experimentation, deployment, monitoring, retraining, and performance optimization.
Drive customer-specific model training and tuning strategies to improve accuracy and adaptability across different customer environments.
Build and improve offline AI evaluation frameworks to measure model quality, drift, effectiveness, and business impact.
Collaborate closely with Engineering, Product, Security, and Data teams to deliver scalable and reliable AI-powered capabilities.
Define best practices for model serving, feature engineering, experimentation, observability, and operational excellence.
Balance model performance, latency, scalability, explainability, and operational constraints in high-scale production environments.
Promote a culture of technical excellence, continuous improvement, ownership, and innovation.

Requirements:
5+ years of experience in Data Science, Machine Learning, or Applied AI roles, with at least 2 years in a leadership capacity.
Strong hands-on experience building and deploying ML models in production environments.
Experience with real-time inference/model serving architectures and low-latency prediction systems.
Deep understanding of model training, evaluation, tuning, and monitoring methodologies.
Experience designing customer-specific ML solutions and personalization strategies.
Strong programming skills in Python and experience with modern ML frameworks and tooling.
Proven ability to lead technical initiatives and guide teams in fast-paced, production-focused environments.
Strong analytical and problem-solving skills with a data-driven mindset.
Excellent communication and cross-functional collaboration skills.

This position is open to all candidates.

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8898014

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