לוח משרות דרושים NLP/Machine Learning

We are seeking a skilled ML Engineer to design, build, and deploy advanced ML solutions that drive analytics, anomaly detection, and data classification across enterprise-scale environments.
This role will focus on developing and optimizing models, including LLMs and prompt engineering pipelines, and ensuring seamless integration into production workflows spanning cloud-native, on-premises, and Databricks ecosystems.
Key Responsibilities :
Design, build, and deploy ML models for user behavior analytics, anomaly detection, and data classification across enterprise environments.
Collaborate with data scientists, software and data engineers to integrate ML models into production pipelines, cloud-native environments, on-premises, and Databricks workflows.
Develop, fine-tune, and evaluate LLMs and prompt engineering solutions for data classification, labeling, and threat analysis features.
Optimize models using techniques like distillation, quantization, and efficient data structures to boost performance and lower resource cost.
Build high-performance data inputs using embeddings, vector databases, and distributed training frameworks.
Manage model lifecycle and performance via MLOps best practices: monitoring, retraining, and deploying updates.
Partner with data scientists, cybersecurity researchers and product teams to evaluate and refine ML-driven capabilities.
Conduct experiments and benchmark results in fast-paced, data-intensive environments.

As a Machine Learning Engineer, youll work on cutting-edge
code-focused LLMs and AI agent systems
that power our companys next-generation developer platform. Youll be at the center of research, model training, and productionization of intelligent systems that understand software deeply, collaborate with developers, and help automate engineering workflows end-to-end. Your work will immediately impact millions of engineers worldwide.
Responsibilities:
Push LLM Innovation: Research, design, and fine-tune domain-specific LLMs for code generation, refactoring, debugging, and multi-turn reasoning.
Agent-Oriented Development: Build multi-agent coding systems that integrate retrieval-augmented generation (RAG), code execution, testing, and tool use to create autonomous, context-aware coding workflows.
Production-Grade AI: Own the training-to-inference pipeline for large code modelsoptimize inference with quantization, distillation, and caching techniques.
Rapid Experimentation: Prototype and validate ideas quickly; leverage reinforcement learning, human feedback, and synthetic data generation to push accuracy and reasoning.
Cross-Functional Collaboration: Partner with product, engineering, and design teams to ship AI-powered features that help developers focus on high-impact work.
Scale the Platform: Contribute to distributed training, scalable serving systems, and GPU/TPU-efficient architectures for ultra-low-latency developer tools.

Required Experienced Software & MLOps Developer for Modeling Group
You will be part of our REM (Road Experience Management) department which is responsible for the automatic High Definition map-making process, which is a key technology in our autonomous driving and high-end Driving Assistance systems.
This process involves running advanced algorithmic code in a massively parallel way, utilizing Big Data technologies, and as such is a complex system that requires a deep understanding of our map creation process as well as advanced technical abilities.
You will be part of our algorithmic teams, being a key team member and owner of development processes.
What will your job look like?
Write clean, modular, and maintainable code in Python to implement algorithms efficiently.
Design and optimize data structures to support algorithmic solutions, ensuring scalability and performance.
Work closely with cross-functional teams.
Write efficient, reliable, and maintainable code to implement algorithms, ensuring high performance and scalability. Debug and troubleshoot software issues as needed.
Contribute to the design and architecture of software systems, ensuring that algorithmic components integrate seamlessly.
Analyze and optimize algorithms for speed, memory usage, and efficiency. Implement parallel processing and optimization techniques to enhance algorithm performance.

As a Senior Machine Learning Engineer, youll play a vital role in turning algorithm prototypes into shippable products that will have a significant and immediate impact on the companys revenue
How youll make an impact:
As a Senior Machine Learning Engineer, youll bring value by:
Be responsible for the entire algorithmic lifecycle in the company: data analytics, prototyping of new ideas, implementing algorithms models in a production environment and then monitoring and maintaining them
Turn algorithm prototypes into shippable products that will have a significant and immediate impact on the companys revenue
Work on a daily basis with some of the hottest trends in todays job market: machine/deep learning, big data analytics/engineering and cloud computing
Apply your scientific knowledge and creativity to analyze large volumes of diverse data and develop algorithmic solutions and models to solve complex problems
Influence directly on the way billions of people discover the internet
Work on projects such as Internet Personalization, Content Feed, Real Time Bidding, Video Recommendations and much more.

As a Senior MLOps Engineer on the Infra group, youll play a vital role in develop, enhance and maintain highly scalable Machine-Learning infrastructures and tools.
How youll make an impact:
As a Senior MLOps Engineer Engineer, youll bring value by:
Develop, enhance and maintain highly scalable Machine-Learning infrastructures and tools, including CI/CD, monitoring and alerting and more
Have end to end ownership: Design, develop, deploy, measure and maintain our machine learning platform, ensuring high availability, high scalability and efficient resource utilization
Identify and evaluate new technologies to improve performance, maintainability, and reliability of our machine learning systems
Work in tandem with the engineering-focused and algorithm-focused teams in order to improve our platform and optimize performance
Optimize machine learning systems to scale and utilize modern compute environments (e.g. distributed clusters, CPU and GPU) and continuously seek potential optimization opportunities.
Build and maintain tools for automation, deployment, monitoring, and operations.
Troubleshoot issues in our development, production and test environments
Influence directly on the way billions of people discover the internet.

As a Staff MLOps Engineer on the Infra group, youll play a vital role in develop, enhance and maintain highly scalable Machine-Learning infrastructures and tools.
As a Staff MLOps Engineer Engineer, youll bring value by:
Develop, enhance and maintain highly scalable Machine-Learning infrastructures and tools, including CI/CD, monitoring and alerting and more
Have end to end ownership: Design, develop, deploy, measure and maintain our machine learning platform, ensuring high availability, high scalability and efficient resource utilization
Identify and evaluate new technologies to improve performance, maintainability, and reliability of our machine learning systems
Work in tandem with the engineering-focused and algorithm-focused teams in order to improve our platform and optimize performance
Optimize machine learning systems to scale and utilize modern compute environments (e.g. distributed clusters, CPU and GPU) and continuously seek potential optimization opportunities.
Build and maintain tools for automation, deployment, monitoring, and operations.
Troubleshoot issues in our development, production and test environments
Influence directly on the way billions of people discover the internet.

Required Experienced Software & MLOps Developer for Modeling Group
You will be part of our REM (Road Experience Management) department which is responsible for the automatic High Definition map-making process, which is a key technology in our autonomous driving and high-end Driving Assistance systems.
This process involves running advanced algorithmic code in a massively parallel way, utilizing Big Data technologies, and as such is a complex system that requires a deep understanding of our map creation process as well as advanced technical abilities.
You will be part of our algorithmic teams, being a key team member and owner of development processes.
What will your job look like?
Write clean, modular, and maintainable code in Python to implement algorithms efficiently.
Design and optimize data structures to support algorithmic solutions, ensuring scalability and performance.
Work closely with cross-functional teams.
Write efficient, reliable, and maintainable code to implement algorithms, ensuring high performance and scalability. Debug and troubleshoot software issues as needed.
Contribute to the design and architecture of software systems, ensuring that algorithmic components integrate seamlessly.
Analyze and optimize algorithms for speed, memory usage, and efficiency. Implement parallel processing and optimization techniques to enhance algorithm performance.

We are looking for a talented Algorithm Engineer to join our Cognitive AI team. In this role, you will design, build, and optimize LLM-based agents that power real-time problem solving. You will be hands-on in Python, research-driven, and passionate about creating intelligent, scalable AI solutions that make a real impact.
Responsibilities:
Design, develop, and optimize LLM-based agents for real-world production use cases.
Build intelligent agent frameworks that orchestrate reasoning across tools, APIs, and knowledge bases.
Deploy and maintain LLM applications in production, ensuring performance, scalability, and reliability.
Research new approaches in LLMs and agent architectures, and integrate cutting-edge techniques into production systems.
Collaborate with cross-functional teams (product, engineering, data) to translate business needs into AI solutions.
Continuously monitor and optimize deployed models, diagnosing and resolving bottlenecks.
Think creatively about complex problems and deliver technological Innovation

We are seeking a hands-on Tech Lead to be the first technical hire for our newly formed ML team. This is a unique ground-floor opportunity to build something from scratch and have direct influence on the technical direction of our ML capabilities. This role combines deep technical expertise with foundational leadership, requiring someone who can architect solutions, establish technical standards, and lay the groundwork for future team growth. As our founding ML tech lead, you'll have the opportunity to shape our technology choices, define our technical practices, and build the fundamental skill set that will guide the team as we scale.
Hybrid
Full-time
What youll do: 
Shape the technical foundation: As our first ML hands on hire, choose and establish the team's core technology stack, frameworks, and development practices together with the ML leader
Build from the ground up: Design and implement our initial ML infrastructure, data pipelines, and model deployment frameworks
Define technical standards: Establish coding standards, best practices, and processes that will guide future team members
Hands-on development: Lead by example through direct development and deployment of ML models and data science solutions
Partner with stakeholders: Work closely with business teams to identify initial ML opportunities and build foundational proof-of-concept models
Establish MLOps practices: Set up our model development, testing, deployment, and monitoring workflows from scratch
Recruit and onboard: As the team grows, play a key role in technical interviews and help onboard new ML engineers and data scientists
Create team culture: Help establish the team's technical culture, learning practices, and collaboration methods
Technology evaluation: Research and select the tools, platforms, and technologies that will form our ML tech stack
Document and share knowledge: Create foundational documentation and knowledge-sharing practices for the growing team.

We are seeking a highly motivated Senior Deep Learning Researcher to join our team! This is an outstanding opportunity to conduct impactful research and develop the next generation of large language model (LLM) inference algorithms. You will work on technologies that directly enhance NVIDIA's software, making the latest LLMs more efficient and accessible for users worldwide. By joining us, you will be part of a strategic effort to establish NVIDIA as the definitive platform for high-performance LLM inference. You will engage with skilled problem-solvers at NVIDIA and top organizations, crafting AI technology advancements.

What you'll be doing:
Research, invent, and implement groundbreaking algorithms for LLM inference to advance the state of the art in both low-latency and high-throughput scenarios.
Translate research into practical software solutions that directly impact NVIDIA's products and customers.
Collaborate with internal research, engineering, and product teams across the globe to drive the development of sophisticated inference technologies.
Analyze the performance of new algorithms on NVIDIAs latest hardware, identifying bottlenecks and opportunities for algorithmic optimizations.
Partner with leading scientific organizations and industry pioneers to remain at the forefront of technological advancements and integrate the latest innovations into practical applications.

Were on a mission to revolutionize how marketers, writers, and innovators create their marketing content. With tools like ChatGPT?? taking the world by storm, its clear that the spotlight is now shining on the Generative AI space. However, its ultimate hurdle is now a self-compounding problem: with infinite options for messaging now available to all marketers how do we know what will actually work? Your words matter, and Anyword was built to ensure that they resonate. Since 2021, weve been building a platform to help both the worlds largest brands and its next rising stars actually move, inspire, and drive their audiences forward. In reality, weve removed the uncertainty of writing performance copy, and are the first to bring copy intelligence into play. Weve combined our own language models, predictive analytics, custom AI, and branding-specific tools to help brands rise above the noise in ways they couldnt before. Weve built the brain behind all marketing messaging, no matter where it lives and how you create it (with AI or not). And now were looking to you to help change the world with us!
About the role Anyword is seeking a senior NLP data Scientist to lead our marketing language predictive modeling. Youll explore complex datasets, build and fine-tune advanced NLP /LLM models, and partner closely with engineering and product to integrate your work into Anywords AI content platform.
Responsibilities:
* Define and own the technical strategy and roadmap for Anywords marketing language predictive modeling.
* Analyze, process, and derive insights from our ever-growing data resources.
* Solve challenging prediction problems by applying the latest ML/ NLP techniques to build and fine-tune highly performant LLMs.
* Collaborate with engineers and product managers to ship models end-to-end, from research to production.
* Monitor and iterate on models using offline and online metrics.

Shape the Future of Cybersecurity with Us Are you driven by curiosity, innovation, and the desire to turn cutting-edge research into real-world impact? Join Cynet, an established but rapidly growing cybersecurity startup, where you'll be part of a small, elite team building groundbreaking AI-powered security products from the ground up. Work alongside top minds in security research, R&D, product, and data engineering to drive innovation and create real value for global customers. This is your chance to contribute to a foundational mission - developing AI technology that proactively protects against today’s most sophisticated cyber threats.

What will you do:
As an ML Engineer at Cynet, you’ll play a central role in shaping our future technology. You’ll: Own AI product creation end-to-end - from the initial concept through building prototypes to full-scale production. Drive innovation by developing and integrating ML and Generative AI solutions into Cynet’s core cybersecurity products: Endpoint, XDR, Network Detection, and Posture Management. Analyze massive volumes of security data to uncover hidden patterns, threats, and insights. Develop and fine-tune models with state-of-the-art optimization strategies and performance metrics. Contribute to and expand our AI infrastructure , including data pipelines, evaluation tools, and deployment frameworks. Conduct rigorous experimentation , explain and monitor the real-world performance of your models. Write production-ready code that makes it into our deployed AI systems.

We are seeking a highly skilled and motivated MLOps Engineer to join our team and play a critical role in the deployment, automation, and maintenance of our machine learning infrastructure. You will be responsible for ensuring that our ML models move seamlessly from experimentation to production with stability, security, and scalability in mind. You will work closely with data scientists, machine learning engineers, and DevOps teams to build robust model pipelines, manage infrastructure across on-prem and cloud, and enforce best practices in version control, model deployment, and compliance. Key Responsibilities: · Design, implement, and maintain automated model training pipelines using tools such as MLflow, (Kubeflow, Airflow), or custom orchestrators. · Support reproducibility and consistency across model training environments. · Implement and manage Artifactory. · Establish and maintain model registries to track versions, metadata, and lineage. · Automate model promotion through staging, testing, and production environments. · Build CI/CD pipelines tailored for ML use cases, integrating model training, validation, deployment, and rollback. · Manage and scale infrastructure across cloud platforms (Azure) and on-premise environments · Optimize GPU/CPU resource utilization and cost efficiency. · Implement auto-scaling and load balancing strategies for ML workloads. · Manage version control systems (e.g., Git) and integrate with experiment tracking tools. · Handle storage and retrieval of artifacts (e.g., Docker images, models, datasets) via artifact registries like JFrog Artifactory or AWS ECR.