LLM Engineer

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8837680

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5 ימים

Senior AI Solutions Engineer

חברה חסויה

Location: Tel Aviv-Yafo and Yokne`am

Job Type: Full Time

We are looking for a talented AI Solutions Engineer to join our innovative AI team. In this role, you will act as a bridge between our AI capabilities and internal customers, helping teams effectively adopt and integrate cutting-edge AI based solutions. Our team develops advanced AI applications including agentic workflows, Retrieval-Augmented Generation (RAG) systems, Large Language Model (LLM) based solutions, AI agents, MCPs, and more. You will play a key role in ensuring these technologies deliver real value by working closely with users and contributing hands-on development. We are looking for a motivated teammate who enjoys working with technology, people and developing new capabilities.

What you'll be doing:

Lead technical engagements to showcase AI capabilities and demonstrate best practices.

Support integration of AI solutions into existing systems and workflows.

Guide users on how to effectively use AI tools and platforms to maximize impact.

Develop and customize AI solutions (e.g., RAG pipelines, LLM-based applications, evaluation, agents, etc.) based on customer use cases while ensuing high reliability.

Troubleshoot technical issues and provide hands-on support during onboarding and adoption.

Requirements:
What we need to see:

B.Sc. (or equivalent experience) in Computer Science, AI, Machine Learning or related field.

8+ years of experience in software development and building production-grade software systems.

2+ years of experience building LLM-based solutions, AI agents, and AI workflows.

Experience working with customers in a technical capacity.

Strong understanding of modern AI/ML concepts and practical applications.

Proficiency in Python.

Excellent people skills with strong communication skills and ability to explain complex technical concepts clearly.

Ways to stand out from the crowd:

Experience with LLMs, RAG systems, or AI agents.

Background in solutions engineering, customer engineering, or technical consulting.

Familiarity with vector databases, embeddings, and evaluation methods.

Ability to quickly prototype and adapt solutions to new use cases.

Strong product thinking and user-centric perspective as well as experience creating demos, POCs, or technical workshops.

This position is open to all candidates.

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8836167

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04/09/2026

Machine Learning Engineering Manager

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

As a Machine Learning Engineering Manager, you will lead a team focused on the foundational ML & Data layers to power the ranking & recommendation systems in scope. You will drive the development of robust data & ML pipelines at scale, lead the implementation of the tools for ML scientists to test and productionize advanced ML RecSys solutions.

As a technical manager of Machine Learning Engineers and Data engineers, you should be passionate about technology, keep up to date with recent breakthroughs in the field, define and shape the teams ML and platforms roadmap, and not be afraid to get your hands dirty with code when needed.

You are expected to be the focal point for all technical aspects, make sure your team members deliver on their tasks, and work together with other stakeholders to define and shape the roadmap of our products. You will work independently and will also be responsible for making technical decisions within your team.

When it comes to management, your expertise in handling people will motivate and inspire them to reach outstanding success! You should have experience in developing people. You will mentor and coach your team while working closely with a Product Manager.

Key Job Responsibilities and Duties:

Lead and develop a high-performing team, fostering individual growth and collaboration.

Manage and mentor ML engineers and Data engineers, ensuring their professional development and effectiveness.

Develop scalable ML infrastructure and pipelines for efficient data processing and evaluations deployment.

Evaluate architecture solutions based on cost, business needs, and emerging technologies.

Collaborate closely with software engineers to ensure seamless deployment and model inference.

Monitor application health, set and track relevant metrics, and implement effective maintenance strategies.

Collaborate with stakeholders to translate business requirements into viable ML solutions.

Evaluate and integrate new ML technologies to enhance productivity and performance.

Requirements:
3+ years leading an ML engineering team of a minimum of 4 people in a fast-paced production environment.

Relevant work or academic experience (MSc + 5 years of working experience, or PhD + 3 years of working experience), involved in the application of Machine Learning to business problems.

Masters degree, PhD or equivalent experience in a quantitative field (e.g. Computer Science, Engineering Mathematics, Artificial Intelligence, Physics, etc.).

Strong knowledge in areas like e.g. Recommender Systems, Deep Learning, Information Retrieval, Causal Inference, scaling ML models, etc.

Experience designing and executing end-to-end solutions for deploying different ML models.

Experience with cloud frameworks like AWS sagemaker for training, evaluation and serving models using TensorFlow, PyTorch, or scikit-learn.

Experience with big data processing frameworks such, Pyspark, Apache Flink, Snowflake or similar frameworks.

Demonstrable experience with MySQL, Cassandra, DynamoDB or similar relational/NoSQL database systems.

Deep understanding of machine learning algorithms, statistical models, and data structures.

Experience collaborating cross functionally in the development of machine learning products (e.g. Developers, UX specialists, Product Managers, etc.).

Strong working knowledge of Python, Java, Kafka, Hadoop, SQL, and Spark or similar technologies. Working experience with version control systems.

Excellent English communication skills, both written and verbal.

Successfully driving technical, business and people related initiatives that improve productivity, performance and quality while communicating with stakeholders at all levels

Leading by example, gaining respect through actions, not your title. Developing your team and motivating them to achieve their goals. Providing feedback timely and managing your key team performance indicators.

This position is open to all candidates.

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8809571

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04/09/2026

Machine Learning Scientist II - GenAI Applications

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

As a Machine Learning Scientist II, you will work within a cross-functional team of engineers and product managers to develop, evaluate, and deploy GenAI-powered solutions for scalable, customer-facing applications. Your work will focus on implementing agentic capabilities, contributing to evaluation frameworks, and delivering measurable business impact through data-driven experimentation.

Key Job Responsibilities and Duties:

Contribute to the design and development of end-to-end agentic systems, ensuring code quality and efficiency in production.

Build agentic solutions for different tasks and use cases using state-of-the-art techniques

Develop and carry out evaluation strategies, including formulating new metrics and building evaluation judges

Adhere to and promote established best practices in GenAI application development within the team.

Collaborate actively with team members, participating in code reviews, sharing knowledge, and contributing to a positive team environment.

Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into ML solutions.

Conduct deep data analysis to evaluate model performance, label quality, features exploration.

Work closely with ML engineers to ensure and improve the solutions latency/throughput meets product requirements and ensure deployment of your model to production.

Requirements:
Bachelors or masters degree in Computer Science, Engineering, Statistics, or a related field.

Minimum of 3 years of experience as a Machine Learning Scientist or a similar role, with a consistent record of successfully delivering ML solutions to production.

Strong understanding and practical experience with Generative AI models, Natural Language Processing and engineering aspects of developing ML.

Experience executing research and development plans and contributing to large-scale ML applications.

Experience on multiple ML facets: working with large data sets, model development, statistics, experimentation, data visualization, optimization, software development.

Experience collaborating cross-functionally in the development of ML products (e.g. Developers, Product Managers, UX specialists, etc.).

Strong working knowledge of Python, LangChain, SQL, and Spark or similar technologies.

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.

Excellent English communication and presentation skills, both written and verbal.

This position is open to all candidates.

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8809569

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10/09/2026

ML Software Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

We are looking for a strong Backend Software Engineer to bridge the gap between our Machine Learning research team and our enterprise production systems. You will act as the technical backbone for our ML Scientists - by advising, designing and implementing the production facing features. If you are a backend expert who wants to solve complex system architecture challenges and dive into the world of ML platforms & Agentic LLM pipelines, this is the role for you - An exciting role collaborating with ML science team, data/infra team and DevOps to drive real customer impact.

As a ML Engineer, you will:

Lead ML delivery: transforming research output (code, models, ideas) into robust, scalable, low-latency microservices in production

Help architect e2e solutions to real customer pains ranging from ingestion, integration, ETLs, DB design up to low-latency services

Design, build, and maintain automated workflows for ML models, including auto-trains, benchmarking, testing, performance gating, and production deployment.

Tackle complex backend challenges: optimizing API response times, managing database connectivity and concurrency at scale, balancing accuracys drive for complex questions with the business needs of fast responsiveness by making hard technical trade-offs between customer gains and business costs.

Design and optimize data pipelines and ETL processes, connecting our Snowflake data warehouse to our training environments.

Work within our existing ML infrastructure (Kubeflow, MLflow, KServe) to ensure smooth model lifecycles and performance monitoring.

Collaborate closely with ML Scientists, guiding them on software engineering best practices without slowing down their research.

Monitor and optimize production models for performance, cost efficiency, availability, and observability.

Requirements:
6+ years of backend software engineering experience designing, building, and maintaining large-scale, high-throughput production systems

Strong coding skills, Ability to write clean, maintainable code, OOP familiarity, package design, microservices etc.
Note: Work is in python, but strong engineers with deep Java/C# backgrounds who have some Python experience and are willing to transition fully are highly encouraged to apply.

Solid Database design & SQL skills, Deep understanding of SQL, experience working with relational and/or bigdata (columnar) databases, ORMs, and efficient query design.

API & Performant Design Proven experience - building robust systems, you understand how to handle concurrency, ETL tradeoffs, building fault-tolerant best effort data flows

This position is open to all candidates.

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8818291

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3 ימים

Senior Applied AI Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

Were looking for a Senior Applied AI Engineer who combines deep data science expertise with the engineering skills to turn research into reliable, production-ready products.
Youll be a hands-on technical leader, owning significant AI capabilities from problem definition, academic survey, and system design through research, experimentation, deployment, and continuous improvement. Your work will span classical machine learning, large-scale data analysis, and AI agents that power brand intelligence, market research, and performance marketing.

You should have a track record of driving complex projects, not just contributing to them, and be comfortable making technical decisions, navigating ambiguity, and delivering in a fast-moving startup environment. Youll build systems that Fortune 500 marketing teams rely on to make consequential business decisions.
Responsibilities
Own AI capabilities end to end. Translate business and product needs into well-defined problems, research plans, and technical designs. Take solutions from initial exploration through production deployment and ongoing improvement.
Develop and improve our core algorithms.
Build production-grade AI agents - performance marketing, market research agents, auto-ML agents.
Turn research into maintainable software. Build reusable modules, data pipelines, and services with clear interfaces, automated tests, and robust deployment practices-not just standalone prototypes.
Own quality and performance in production. Monitor system behavior, investigate failure cases, and continuously improve accuracy, reliability, latency, and cost as usage and data volumes grow.
Drive technical decisions and execution. Choose the right approach for each problem, balancing statistical methods, classical ML, and LLM-based systems. Make explicit trade-offs between research depth, delivery speed, and operational complexity.
Provide hands-on technical leadership. Partner with product and engineering to shape priorities, lead technical initiatives, review designs and code, and mentor teammates.

Requirements:
MSc or PhD in Computer Science, Data Science, Statistics, Mathematics, or a related quantitative field.
5+ years of experience in data science or applied machine learning, plus 2+ years in ML engineering or software engineering, with direct responsibility for deploying and maintaining production systems.
Proven ownership of significant AI products or features. You have been a primary technical driver, taking ambiguous problems from initial concept to a working product used by real customers.
Strong foundations in machine learning and statistics, including experimental design, model evaluation, and practical experience with NLP, embeddings, clustering, or related methods for analyzing unstructured data.
Strong Python, SQL and Typescript skills, alongside solid software engineering practices: modular architecture, automated testing, version control, code reviews, and maintainable production code.
Hands-on experience building LLM-powered applications or AI agents beyond the prototype stage, including tool calling, structured outputs, context management, and systematic evaluation
Experience deploying and operating systems in a cloud environment, including containerization, CI/CD pipelines, logging, monitoring, and debugging production issues.
Strong product judgment and independent execution. You can define milestones, prioritize experiments, communicate technical trade-offs, and collaborate effectively across product, engineering, and business teams in a fast-moving environment.
Advantage
Experience as a core technical contributor at a high-growth startup, building new products and scaling them as adoption grows.
Experience in advertising technology, marketing analytics, search, information retrieval, ranking, or recommendation systems.
Familiarity with agent frameworks and SDKs such as ADK, LangChain, or comparable tooling.

This position is open to all candidates.

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8837997

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24/09/2026

AI Developer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

Were looking for a highly motivated AI Developer to help design, build, and deploy intelligent agentic systems across our product ecosystem. In this role, you'll work at the intersection of machine learning, backend systems, and modern frontend technologies to deliver AI-first features that feel magical to users.

This is a hands-on, cross-functional role ideal for engineers who love building full-fledged features-from data pipelines and LLM orchestration to intuitive UI experiences-with a strong product mindset.

Responsibilities:
AI Agent Design & Integration
Design and implement autonomous or semi-autonomous agents using LLMs (e.g., OpenAI, Anthropic, open-source models).
Work with prompt engineering, RAG pipelines, and tool/plugin integrations to enable agents to interact with internal and external systems.
Build scalable agent runtimes and orchestration layers (e.g., LangChain, Semantic Kernel, ReAct-based agents).
Fullstack Product Development
Own full-stack features end-to-end: from backend APIs and data models to React-based frontend interfaces.
Integrate AI/agent capabilities into customer-facing products with clean UX and measurable performance.
Collaborate closely with design, product, and data teams to bring ideas from concept to production.
Systems & Infrastructure
Build and maintain backend services and pipelines that support AI agents, including vector search, embeddings, function calling, and observability.
Optimize inference flows for performance and cost, potentially using streaming, caching, or local model inference.
Ensure systems are secure, reliable, and compliant with InfoSec standards.
Experimentation & Continuous Improvement
Rapidly prototype and iterate on new AI capabilities and user experiences.
Analyze performance and usage metrics to drive product and model improvements.
Stay up to date with the evolving AI toolchain and emerging agent architectures.

Requirements:
8+ years of fullstack development experience with strong skills in TypeScript/JavaScript, React, and Python (or Node/Go for backend).
Solid understanding of LLM APIs, agent frameworks (e.g., LangChain, AutoGPT, CrewAI), or custom AI pipelines- Advantage
Experience with modern cloud infrastructure (e.g., AWS, GCP, Docker, CI/CD).
Familiarity with vector databases (e.g., Pinecone, Weaviate, FAISS) and retrieval-augmented generation (RAG)- Advantage
Product-oriented mindset: you care deeply about building things that work well for users.
Bonus: experience with observability, feedback loops for AI agents, or embedded AI evaluation techniques.

This position is open to all candidates.

עדכון קורות החיים לפני שליחה

8832909

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3 ימים

AI Builder

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

Were looking for an AI Builder to serve as the technical backbone of Nomas internal AI function. Youll build the LLM-powered agents, automation pipelines, integrations, and infrastructure that teams across the company rely on every day.

This is a rare opportunity to build a new function from the ground up within a company where the work can have an immediate and meaningful impact. Youll create systems such as tools that help Sales track competitive deals in real time, pipelines that automatically turn customer calls into Salesforce updates, and agents that identify competitor activity and deliver actionable insights directly to Slack.

This is a highly hands-on role with true end-to-end ownership-from translating business needs into focused technical solutions to deploying, monitoring, and continuously improving production systems.

What Youll Do:

Build AI-Powered Agents and Automations
Design and build LLM-powered agents, automation pipelines, and backend services used across the organization.
Develop complex integrations that bring together data from multiple internal and external systems.
Build custom MCP servers and other infrastructure required to support scalable internal AI workflows.
Turn fuzzy business needs into practical, focused, and maintainable technical solutions.

Own the Internal AI Infrastructure
Harden and maintain Nomas existing MCP Gateway ecosystem.
Improve reliability, error handling, authentication, secrets management, and versioning.
Implement secure, vault-based credential management and strong security practices across production automations.
Build infrastructure that enables agents and workflows to operate reliably at scale.

Drive Production Readiness and Reliability
Own the deployment, monitoring, maintenance, and reliability of agents and automations in production.
Build evaluation frameworks, test sets, and monitoring processes to measure accuracy, precision, recall, hallucination rates, and overall agent performance.
Identify regressions and continuously improve the quality and stability of production workflows.
Troubleshoot failures across integrations, mod

דרישות:
What You Bring:
3-5 years of software engineering or hands-on development experience.
Strong Python skills and experience writing clean, maintainable, production-grade code.
Hands-on experience working with LLM APIs such as Anthropic Claude, OpenAI, or similar.
Experience building integrations using REST APIs, webhooks, and asynchronous pipelines.
Experience with automation platforms such as n8n, Make, Zapier, or similar.
Hands-on experience with MCP and building or integrating MCP servers.
Experience evaluating LLM or agent performance in production, including building evaluation harnesses or test sets to identify regressions.
Understanding of secrets management, credential handling, and security best practices for production automations.
Ability to work independently and own projects end-to-end.
Strong problem-solving skills and the ability to turn ambiguous requirements into practical technical solutions.

Who You Are:
Genuinely excited about AI and actively following developments in the space.
Adaptable by default-you learn quickly, pivot when needed, and dont become overly attached to a specific tool or approach.
You ship quickly, gather feedback, and iterate.
You care about the end user and business impact, not only the technology.
Comfortable working in a fast-moving startup environment without an established playbook.
Highly accountable, hands-on, and motivated by building something from the ground up.

Nice to Haves:
Background in cybersecurity or enterprise B2B SaaS.
Experience with agent frameworks such as LangChain, LangGraph, CrewAI, or equivalent.
Experience building internal developer platforms or company-wide automation infrastructure.
Familiarity with Salesforce, Slack, and other common enterprise systems.
Experience driving internal adoption of AI tools and המשרה מיועדת לנשים ולגברים כאחד.

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8838238

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6 ימים

Principal/Senior ML Platform Engineer (Cortex)

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

We are looking for a Principal MLOps Engineer with a deep focus on ML Platforms and Infrastructure to join our Data & AI group at Cortex Research. Our team is responsible for designing, building, and scaling the foundational MLOps and LLMOps platforms that power both our Data Scientists and Security Researchers. You will architect the high-performance core infrastructure that enables these roles to build, train, and deploy advanced AI systems-ranging from optimized Small Language Models (SLMs) to complex agentic workflows and RAG systems. If you are passionate about building scalable compute platforms and automating the full ML lifecycle to solve complex data and security challenges, we want to hear from you.
Key Responsibilities
Scale Distributed Training: Design and optimize infrastructure for training and fine-tuning LLMs and SLMs, leveraging distributed GPU workloads, efficient clustering, and compute optimization.
Automate the ML Lifecycle: Architect robust, automated pipelines for continuous training (CT) and deployment (CD) of models, ensuring a seamless flow from raw data collection to production environments.
Build Model Infrastructure: Own the serving architecture for LLMs/SLMs, balancing latency, throughput, and GPU utilization under production traffic.
Implement Advanced Monitoring: Establish comprehensive observability systems to monitor live model performance, data drift, and computational metrics, feeding insights back into the automated training loops for continuous improvement.
Collaborative Architecture: Partner closely with data scientists and security researchers to productize complex model architectures and streamline their workflows, while collaborating with our DevOps team to integrate with core cloud infrastructure.

Requirements:
Required Qualifications
Core Engineering: 4+ years experience as a Senior ML Engineer, MLOps Engineer, or Backend Platform Engineer (Hands-On) working with cloud environments.
Model Lifecycle Engineering: Hands-on experience managing the technical lifecycle of diverse model architectures, spanning classic ML, LLMs/SLMs, and agentic/RAG systems. This includes engineering scalable data preparation and processing pipelines as well as implementing infrastructure for model training, fine-tuning, optimization, and high-throughput production serving.
Distributed Training & Compute: Strong foundational knowledge of Deep Learning concepts (neural network architectures, training dynamics, optimization techniques) paired with proven experience setting up and optimizing distributed training workloads across multiple GPUs (using PyTorch, DeepSpeed, Megatron-LM, or cloud-native training infrastructure).
Cloud & Infrastructure Architecture: Strong infrastructure knowledge within a major cloud provider ecosystem (GCP, AWS, or Azure), specifically leveraging managed AI platforms and services.
Python Expertise: Expert-level Python skills focused on ML infrastructure, pipelines, and automation frameworks.
CI/CD Integration: Experience with modern CI/CD patterns (such as GitLab CI or GitHub Actions) for automating software and model delivery loops.
AI Tooling & Development: Proficient in leveraging day-to-day AI tools and ecosystems (e.g., Claude, Gemini, MCPs, custom skills, and markdown formatting) to generate, review, and test code dynamically within your development cycle.
Preferred Qualifications
Strong GCP ecosystem experience.
Background in data science or deep learning workflows.
Cybersecurity domain knowledge.

This position is open to all candidates.

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אירעה שגיאה בשליחת פרטיך למשרה

25/08/2026

AI Data Quality Analyst (Paradox)

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

Are you an analytical person who is deeply interested in AI and LLM technology?
Is your superpower accurately categorizing information and identifying patterns?
Do you love to solve interesting challenges and make a direct impact through your work?
Join our Tel Aviv team as an AI Data Analyst and help shape the future of AI. We're looking for analytical minds to contribute to our cutting-edge Large Language Model (LLM) project. In this unique role, you'll be performing LLM data quality tasks, ensuring consistency and quality in our conversations and helping design and support our flagship products.
This is more than a traditional data-labelling role. You will combine hands-on evaluation work with analytical thinking to help shape how our AI experiences evolve.
Sound like your perfect fit? We want to hear from you!
As an AI Data Quality Analyst, you will evaluate LLM-generated conversations and other text-based data, identify trends and regressions, and partner with AI Engineers and Product Managers to improve model performance. In this role, you will:
Review and evaluate LLM-generated conversations and other text-based outputs against task-specific quality criteria and success metrics.
Perform high-quality annotation and data labeling to create reliable datasets for model training, benchmarking, and evaluation.
Monitor real production data to identify quality trends, regressions, and areas for improvement.
Identify qualitative patterns, recurring failure modes, regressions, and opportunities to improve model behavior and user experience.
Analyze evaluation results and clearly communicate insights, risks, and recommendations to cross-functional stakeholders.
Work closely with our AI Engineers and Product Managers to understand the data needs and ensure data quality processes align with goals, ensuring Paradox and our company products remain top in class.

Requirements:
Experience with data labeling or annotation, ideally involving textual data, conversational data, or generative AI.
Strong qualitative research and analytical skills, with the ability to detect meaningful patterns in large volumes of textual data.
Strong attention to detail, sound judgment, and a high bar for consistency and quality.
Creative, out-of-the-box thinking and a proactive approach to investigating ambiguous or unexpected model behavior.
Technical curiosity and confidence working across web-based tools, labeling platforms, dashboards, and evolving internal interfaces.
Strong English fluency, both written and verbal communication
A research-oriented background, such as Linguistics, Human-Computer Interaction, Cognitive Science, Psychology, or a related field.
Ability to work as from our company Tel Aviv, Israel office location.
Nice to Have:
Experience working directly with LLM analysis, model evaluation, conversation quality assessment, or related AI quality workflows.
Hands on experience using AI tools such as Claude Code, Cursor, or similar tools.

This position is open to all candidates.

עדכון קורות החיים לפני שליחה

8797023

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שמך המלאמה השם שלך?

מייל

תיאור

שליחה

תודה על שיתוף הפעולה

מודים לך שלקחת חלק בשיפור התוכן שלנו :)

המשרה נמחקה

תוכל לצפות בה בדף המשרות שלי

המשרה הוחזרה לרשימת תוצאות החיפוש

האם תרצה להסיר את המשרה מרשימת

המשרות השמורות שלך?

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אירעה שגיאה בשליחת פרטיך למשרה

04/09/2026

Senior Machine Learning Engineer I - GenAI Applications Teams

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

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.

עדכון קורות החיים לפני שליחה

8809567

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