לוח משרות דרושים NLP/Machine Learning

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
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.

Required ML-Engineering Lead
Our people are our greatest strength - and technology is our passion. Our team of innovators and subject matter experts, including veterans of elite military intelligence technology units, is transforming the way organizations protect themselves from drone threats.
As the global leader in cyber-takeover counter-drone technology, we design and deliver advanced, software-defined solutions that empower our customers to detect, take control, and safely land unauthorized drones - with precision and reliability.
Every day, we push the boundaries of innovation to meet real-world security challenges across industries and environments. Were proud of our cutting-edge technology, our global reach, and the impact we make in securing the skies.
Were seeking passionate professionals who thrive in a fast-paced, creative, and collaborative environment - those who want to be part of the next generation of airspace security innovation.
Join us and help make the world a safer place.
Work with the worlds leading cyber-takeover counter-drone technology provider and shape the future of safe airspace.
The Opportunity
We are starting a new ML/AI organization directly reporting to the CTO, to pioneer next-generation capabilities for our industry-leading defense systems. As a Founding ML-Engineering Lead, you will be the technical cornerstone of this initiative. This is a high-impact role designed for a practitioner who seeks total technical ownership of the machine learning lifecycle. You will be responsible for taking novel AI projects from initial concept through data collection, design, implementation, and evaluation, all the way to deployment.
The Technical Challenge Our ML initiatives span a diverse technical landscape. You will lead projects that range from field-oriented applications, where high accuracy and reliability are paramount, to research-oriented tools and agentic workflows designed to enhance our R&D capabilities and accelerate complex data analysis. Working in deep collaboration with our R&D teams, you will leverage unique, proprietary data to solve problems at the forefront of the counter-drone industry.
What You Will Do:
End-to-End Ownership: Lead the full technical execution of ML projects, ensuring every stage-from data acquisition to deployment-meets our rigorous standards.
R&D Collaboration: Partner closely with R&D departments to design data collection strategies and integrate ML-based tools and agents into their specialized workflows.
Versatile Implementation: Develop models and intelligent systems for a variety of use cases, ranging from real-time field performance to autonomous research-support tools.
Technical Authority: Act as a founding voice for ML implementation and strategy within the CTOs office.

We are looking for a Research Team Lead to establish and lead a cross-product research team focused on horizontal, high-impact initiatives that influence multiple offerings.
Unlike product-embedded research roles, this team drives foundational and strategic research projects across networking, security, identity, automation, and AI-driven capabilities. Examples include large-scale reasoning systems, autonomous policy frameworks, cross-domain detection and response concepts (xOps), and platform-wide intelligence capabilities.
You will combine deep technical expertise with strong leadership and execution skills -identifying impactful research directions, building a high-performing team, and turning advanced research into real platform capabilities used by thousands of customers worldwide.
Responsibilities
Technical Vision & Strategy:
Define and execute the roadmap for cross-product research initiatives.
Identify high-leverage research opportunities that impact multiple domains and products.
Drive long-term architectural thinking and influence platform evolution.
Balance innovation, experimentation, and production-readiness.
Team Leadership:
Recruit, mentor, and grow a multidisciplinary team of researchers (AI, data, algorithms, networking, security).
Establish high standards for research rigor, experimentation methodology, and engineering quality.
Foster a culture of ownership, collaboration, and technical excellence.
Research & Execution:
Lead complex, ambiguous research initiatives from ideation through validation and productionization.
Design large-scale experiments and validation methodologies using our data platform.
Drive innovation in areas such as:
Autonomous policy systems
Cross-domain detection and response frameworks
Large-scale reasoning and decision systems
Data-driven optimization and automation capabilities
Ensure research outcomes are measurable, scalable, and aligned with business impact.
Cross-Functional Collaboration:
Work closely with Product, Engineering, Architecture, and Product Research teams to translate research into shipped capabilities.
Provide technical guidance and influence cross-organizational decisions.
Act as a bridge between exploratory research and production systems.
Communication & Influence:
Present research findings and strategic recommendations to senior leadership.
Produce clear technical documentation, design proposals, and internal position papers.
Represent Platform Research as a center of excellence for cross-product innovation.

Were hiring an AI Backend Engineering Manager to guide and grow a high-impact ML team driving AI-powered innovation across B2B SaaS platform. Youll lead the design and delivery of AI solutions while mentoring engineers and setting the technical direction for AI-first development at scale.
This is a leadership role with a balance of hands-on engineering and team management, perfect for someone who thrives on solving technical challenges, inspiring a team, and shaping the future of AI in fintech automation.
What You Will Do:
Lead & Mentor: Manage, mentor, and grow a team of AI/ML/Backend engineers, fostering technical excellence and career development.
Set Technical Direction: Define the ML strategy, ensuring best practices in architecture, frameworks, and operationalization.
Build and deploy AI-based solutions: Oversee the development and deployment of GenAI/LLM-powered solutions that address real-world challenges across products.
Scale & Operationalize: Establish scalable ML infrastructure, CI/CD, observability, and data pipelines for high-availability production systems.
Collaborate Cross-Functionally: Partner with product managers, engineers, and business stakeholders, clearly communicate progress, challenges, and outcomes.

we are looking for an experienced Data Science Manager to lead and grow our Data Science team. This is a managerial role focused on leading a team of Data Scientists while driving the strategy, execution, and delivery of impactful AI and ML initiatives across our SaaS platform.
You will be responsible for both people leadership and technical direction - ensuring high standards of execution, mentoring team members, and aligning data science efforts with product and business goals. This role requires a strong hands-on background combined with proven team management experience.
What You Will Do:
Lead, mentor, and manage a team of 7-10 Data Scientists, fostering a culture of ownership, excellence, and continuous learning.
Own the teams roadmap, prioritization, and delivery of AI initiatives.
Provide technical and architectural guidance across projects.
Drive end-to-end execution of data science solutions - from problem definition and research to modeling, evaluation, deployment, monitoring and enhancement cycles.
Collaborate closely with Product, Engineering, and Business stakeholders to translate business needs into scalable AI solutions.
Ensure production-grade standards, model performance monitoring, and continuous improvement.
Stay up to date with advances in machine learning, GenAI, and LLM technologies, and translate them into business impact.
Take responsibility for hiring, onboarding, and developing top data science talent.

Lead the charge in transforming our product and preparing it for the agentic age.
Design, build, and deploy generative AI-powered features across our product.

Identify opportunities for AI integration by proactively exploring FinOps use cases and user needs

Prototype and validate new AI use cases quickly and iterate based on internal and external feedback

Collaborate cross-functionally with product, design, and backend teams to drive innovation from concept to production

Stay current with the fast-moving generative AI landscape and evaluate new models, APIs, and tools (e.g., OpenAI, Anthropic, Hugging Face, AWS Bedrock, open-source LLMs).

Live in the future and track new innovations and paradigms in this fast evolving field and identify opportunities to integrate them into the product

Implement safeguards, prompt engineering techniques, and usage monitoring to ensure high-quality AI outputs

Optimize model performance, inference time, and cost efficiency within AWS infrastructure

Do you want to take part in shaping the future of AI-driven materials discovery? We are seeking a talented and highly motivated student for a Joint PhD at Bar-Ilan University (BIU), to conduct cutting-edge research in collaboration with our teams, on next-generation Foundation Models for Materials Science.
The work will focus on developing novel multi-modal foundation models for materials discovery, leveraging large-scale data, representation learning, and uncertainty estimation. The candidate will work closely with academic and industry researchers, contributing to both methodological advances and real-world impact across scientific and industrial domains.
What youll be doing:
Conduct research in deep learning and AI for materials science, with a focus on foundation models, multi-modal learning, and representation learning.
Develop and train large-scale models for materials discovery and prediction tasks.
Collaborate with researchers and engineers across and academia.
Lead independent research under academic supervision, while contributing to team efforts.
Publish results in top-tier conferences and journals, and present findings clearly and effectively.

We are looking for a Software Engineer specializing in ML systems Engineering to join Development department.
While vision and language models have become increasingly commoditized, proprietary deep learning models are unique, fast-evolving, and deployed in live trading across the worlds most efficient and sophisticated financial markets. Operating in this environment presents distinct scaling challenges and continuous opportunities for optimization. Success in this role requires first-principles thinking and a deep understanding of the engineering trade-offs behind high-performance DL systems.
This is a pivotal role within engineering organization. You will work closely with researchers and engineers across the company, running deep learning models on massive compute clusters and adapting them for production serving under strict and non-trivial constraints.

Our unique research team is expanding, we are looking for smart and humble team members to join the team and solve complex problems.
Our technical challenges include developing new trading strategies, , improving the performance of our algorithms, finding new ways to beat the markets.
As an ML researcher you will collaborate with our R&D team to execute live trading strategies. If you are looking to make an impact by putting into practice successful ideas and seeing immediately the outcome, make influence on financial performance this is a great opportunity.

We are always looking for exceptional talent to join us on the journey!
We are always looking for exceptional talent to join us on the journey!


Your Mission

As an MLOps Engineer at Nuvei, your mission is to design, build, and operate the platforms that power our machine learning and generative AI products spanning real-time use cases such as large-scale fraud scoring, MCP & agentic workflows support. Youll create reliable CI/CD for models and Agents, robust data/feature pipelines, secure model serving, and comprehensive observability. You will also support our agentic AI ecosystem and Model Context Protocol (MCP) services so that models can safely use tools, data, and actions across .
You will partner closely with Data Scientists, Data/Platform Engineers, Product, and SRE to ensure every model from classic ML to LLM/RAG agents moves from prototype to production with strong reliability, governance, cost efficiency, and measurable business impact.
Responsibilities:
Operate & Develop ML/LLM platforms on Kubernetes + cloud (Azure; AWS/GCP ok) with Docker, Terraform, and other relevant tools
Manage object storage, GPUs, and autoscaling for training & low-latency model serving
Manage cloud environment, networking, service mesh, secrets, and policies to meet PCI-DSS and data-residency requirements
Build end-to-end CI/CD for models/agents/MCP tooling (versioning, tests, approvals)
Deliver real-time fraud/risk scoring & agent signals under strict latency SLOs.
Maintain MCP servers/clients: tool/resource definitions, versioning, quotas, isolation, access controls
Integrate agents with microservices, event streams, and rule engines; provide SLAs, tracing, and on-call runbooks
Measure operational metrics of ML/LLM (latency, throughput, cost, tokens, tool success, safety events)
Enforce governance: RBAC/ABAC, row-level security, encryption, PII/secrets management, audit trails.
Partner with DS on packaging (wheels/conda/containers), feature contracts, and reproducible experiments.
lead incident response and post-mortems.
Drive FinOps: right-sizing, GPU utilization, batching/caching, budget alerts.

We are looking for a Senior Software Engineer to join our Video/Multimedia Architecture & Algorithms (A&A) team - the people who build tomorrows NVENC and NVDEC, the dedicated video encode and decode engines that power streaming, cloud gaming, video conferencing and broadcast on every modern GPU. You will lead the infrastructure and operations for this groups work. This includes setting up compute resources on-premises and in the cloud. You will develop distributed pipelines for large-scale regressions and experiments across hardware simulations and machine learning workloads. You will maintain the CI/CD and development environments. You will also transform one-off research workflows into reliable, repeatable, automated systems.
This is a hybrid role - 4 days per week from the office.
What You'll Be Doing
Work closely with our Architects and Algorithms Engineers to understand the needs and transform one-off research workflows into dependable, consistent, automated systems
Stand up and operate the compute the group runs on - on-prem GPU clusters, cloud bursts, queues, schedulers (Slurm / Kubernetes), container images, environments
Develop and build decentralized workflows for extensive regression testing and experiments across HW-simulations and ML workloads - and the dashboards that make sense of the results
Lead the teams CI/CD plus the dev environments, container images and tooling everyone in the group lives in every day.

Were looking for a seasoned and driven Team Lead to head our NLP & Speech team. In this role, youll lead a high-performing team of researchers and engineers developing state-of-the-art capabilities in real-time transcription, semantic understanding, content generation, and AI-powered editing tools. Leveraging our unique access to vast multimodal datasets and large-scale compute, your team will drive ambitious applied research projects from concept to deployment - powering intelligent, intuitive experiences for millions of content creators.

we are looking for a Senior Machine Learning Engineer to work on LLM-based systems with a strong emphasis on integration, end-to-end workflows, and production readiness. This role combines performance optimization (prefill/decode, throughput, latency) with hands-on work integrating components across the AI platform.
A significant part of the role involves building end-to-end integration flows and tests, particularly around token generation pipelines and system orchestration, as well as contributing to intelligent system behavior such as hardware selection and execution strategies. The role also includes developing system-level logic in Python for multi-tenant management, caching strategies, and service lifecycle management across the platform.
***This is not a Data Science position***
Responsibilities:
Build and maintain end-to-end integration flows across the AI inference pipeline (serving, orchestration, APIs, and infrastructure)
Design, implement, and optimize LLM inference workflows, including prefill and decode stages
Improve system performance with focus on throughput, latency, and interactivity
Write production-grade components in Python and integrate them into the broader system
Contribute to system-level logic such as smart hardware selection and execution strategies
Integrate models (open source and custom), services, and APIs into cohesive, reliable end-to-end application pipelines

Required Staff Software Engineer, Cloud Storage, AI/ML
Tel Aviv, Israel
Responsibilities
Design and implementation of high-complexity features. Deliver production-ready code for storage solutions that address the specific demands of AI/ML workloads.
Architect scalable and performant storage solutions. Make data-driven decisions to optimize system efficiency and reliability.
Identify and resolve performance bottlenecks and intricate system issues. Develop innovative, practical solutions to technical issues that arise at the intersection of storage and ML.
Partner with product and engineering stakeholders to translate customer requirements into technical specifications, ensuring the incubations output aligns with broader Cloud goals.