לוח משרות דרושים NLP/Machine Learning

We are seeking an exceptional senior-level Python engineer to join a small team working on complex data pipelines, AI/ML systems, and cutting-edge software solutions. This role will be responsible for managing technical objectives, providing technical leadership, and maintaining a hands-on approach to development. The ideal candidate will work closely across teams within as part of our business-facing technology organization.
A successful candidate will possess deep expertise in Python development, data engineering, software architecture, and design principles. They should be able to mentor junior team members, conduct code reviews, and drive architectural decisions. Experience with AI and large language models (LLMs) is highly desirable.

Technical teams are overwhelmed by manual, repetitive tasks, fragmented tools, and rapidly growing data. These challenges increase errors, slow decision-making, and prevent teams from focusing on strategic initiatives.
What You'll Do:
Build and deploy clusters of AI agents that tackle multiple use cases across the IT domain.
Work hands-on with LLMs-installing, running, and fine-tuning models. We are not just calling APIs.
Build backend services for data ingestion, AI pipelines, and integrations.
Integrate open-source AI modules directly: read, tweak, and ship.
Operate in AWS (Lambdas, APIs, infrastructure) to power AI-driven features.
Collaborate directly with customers-strong English communication is essential.

Were looking for a Generative AI Developer to join our forward-thinking engineering team. This role is perfect for someone with a passion for cutting-edge AI, a strong software engineering background, and the creative spark to identify and implement novel use cases within our product.

You will play a critical role in adding AI capabilities to our FinOps SaaS platform. Whether it's enhancing user workflows, automating insights, or inventing entirely new product experiences, youll have both the freedom and support to experiment and execute.

provides a uniquely rich dataset covering the full scope of a companys cloud spend. This expansive data playground offers a powerful foundation for experimentation and insight generation, enabling the development of intelligent, value-driven features.

Responsibilities:
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

If youre looking to build something big, solve real problems, and grow fast-wed love to meet you.

You will own AI infrastructure and agentic interaction layer on top of our Data Platform.

The data layer is the product.
The AI layer is the multiplier.
The interaction model between them is the future.

Your responsibility is to design and build:

The AI infrastructure that enables safe, scalable, production-grade AI features

The ability to interact with Data Layer through LLMs and agentic workflows

Guardrails, governance, and system boundaries for AI-driven data access

The foundations that allow AI to be powerful without compromising correctness or trust

We are looking for an AI Engineer to play a central role in building, evaluating, and advancing Immunais AI models. You will own and evolve Immunais benchmarking and evaluation capabilities for foundation models and multimodal systems, while also working closely with modeling teams to support model development, iteration, and validation. This role sits at the intersection of software engineering, model understanding, and applied AI, with broad influence on how models are built, compared, and improved across the organization.

Location: Ramat Gan, Israel (hybrid model)

What will you do?

Own & Evolve Benchmarking - Design, build, and maintain Immunais benchmarking suite for foundation models and multimodal AI systems.
Define Core Abstractions - Create clean, extensible abstractions and APIs for datasets, tasks, models, metrics, and evaluation workflows.
Develop Metrics & Evaluations - Implement metrics that capture predictive performance, biological relevance, and multimodal alignment.
Support Model Development - Work closely with AI scientists and data scientists to integrate new models, tweak architectures, and enable rapid, fair iteration.
Bring in New Models & Baselines - Add external and internal models to benchmarks and ensure meaningful comparisons.
Explore Data When Needed - Dive into data and results to debug evaluations, understand model behavior, and unblock modeling work.
Enable Rigor & Reproducibility - Ensure evaluations are consistent, well-versioned, and trustworthy over time.

As the Product Manager for the AI models of core product offering, you will be responsible for defining and driving its product strategy, requirements, roadmap and delivery.

The product focuses on addressing real-world challenges in drug development by leveraging AI foundation models and multi-omic data to map and predict human immune response.

You will be working closely with our team of Data Scientists, Computational Biologists, Deep Learning Researchers and Engineers.

Location: Ramat Gan, Israel (Hybrid model)

What will you do?

Set the long-term vision and strategy for AI models, ensuring alignment with company goals.
Define product requirements and build a clear, prioritized roadmap for model development and delivery.
Lead benchmarking efforts to evaluate model performance against internal baselines and external best-in-class models.
Collaborate with AI research, data science, engineering, and biologists to translate scientific advances into scalable product capabilities.
Oversee the end-to-end lifecycle of AI models, including data strategy, training priorities, evaluation criteria, releases, and post-deployment monitoring.
Identify, validate, and prioritize high-impact use cases where improved model capabilities create meaningful business or scientific value.
Communicate strategy, progress, and key decisions to leadership and cross-functional stakeholders to drive alignment.

We are looking for a driven and experienced leader to manage a growing interdisciplinary team of LLM Agentic AI Researchers, Computational Biologists, and Immunologists. This teams mission is to build a cutting-edge agentic reasoning system powered by Large Language Models (LLMs), capable of generating structured, biologically grounded sequential explanations based on predictions from proprietary foundation model-trained on hundreds of millions of immune cells. The product the team builds is a pillar of AI strategy, with the potential to redefine the way a drugs mode of action is understood.

Location: Ramat Gan, Israel (hybrid model)

What You'll Do:

Set the Vision - Collaborate with product leadership to transform bold ideas into AI capabilities that impact real-world medical decisions.
Build and Lead the Team - Coach, build and inspire a high-caliber team across LLMs, data science, and Immunology. Cultivate a culture of excellence, curiosity, and execution.
Drive Innovation - Lead from the front-design architectures, write prototypes, and guide technical direction. Lead the team in building agents that reason about biological systems at scale.
Ship Transformative Products - Deliver AI products & solutions that move the needle and its partners - from static biological associations to dynamic, explanatory models of causality.
Showcase Leadership - Represent the team in top-tier scientific conferences and publications, communicating groundbreaking research to the world.

Were looking for an Applied Data Scientist to help us build and scale the core marketing science products that power our platform. This role sits at the intersection of data science and engineering: owning statistical models end to end, deploying them into production, and turning advanced analytics into reliable, customer‑facing capabilities. Your work will directly influence how thousands of brands measure ROI and allocate millions in marketing spend.

What Youll Do:
Build marketing measurement and optimization products (e.g., attribution models, MMM, incrementality testing, forecasting systems)
Develop and deploy statistical and machine learning models to production
Create scalable data pipelines and APIs that serve real-time analytics
Partner closely with Product, Engineering, and other stakeholders to translate business questions into clear analytical solutions.
Own features end to end from statistical design and validation through deployment, monitoring, and iteration.

As a ML Engineering Team Lead at our company, you will lead a multidisciplinary team of algorithm and software engineers responsible for designing, building, and operating the next-generation content creation engine. The team focuses on leveraging agentic systems and advanced ML technologies to orchestrate complex, end-to-end production workflows at scale.
In this role, you will translate high-level product and business goals into robust, production-ready solutions, working hands-on across the full lifecycle - from research and system design to deployment, monitoring, and continuous improvement. You will collaborate closely with Product, Platform, Data, and other R&D teams in a fast-paced, agile environment, ensuring that algorithms and software are seamlessly integrated into real-world, high-throughput systems.
You will combine technical leadership, architectural thinking, and people leadership to drive innovation, execution, and delivery, while shaping how intelligent, automated content is created and scaled across our companys products.
What youll do:
Lead and mentor a multidisciplinary team of algorithm and software engineers, fostering ownership, technical excellence, and professional growth.
Own the delivery of complex, end-to-end systems for automated content creation, from early design and experimentation through production deployment, monitoring, and iteration.
Drive the design and orchestration of agentic systems, working hands-on with the team to integrate ML models, business logic, and software infrastructure across research, engineering, and production at scale.
Translate product and business challenges into technical solutions, defining system architecture, prioritizing initiatives, and guiding execution in an agile environment.
Ensure production readiness and reliability, overseeing deployment, monitoring, performance, and continuous improvement of algorithms and services in a live environment.
Collaborate closely with Product, Platform, Data, and other R&D teams, aligning technical execution with product strategy and business goals in a multidisciplinary setting.
Continuously evolve technically and professionally, encouraging knowledge sharing, joint problem-solving, and awareness of emerging trends in ML, agentic systems, and large-scale software architectures.

we are looking for a Senior NLP Algorithm Developer to join us in research and development of our next-generation automatic sports video content engine. If you are passionate about state-of-the-art NLP and Generative AI research - we are looking for you!
What youll do:
The teams main focus: NLP & Generative AI.
Research and develop end-to-end real-time solutions for sports content generation automation using state of the art deep learning algorithms for text, speech, vision, audio and data analysis.
Full R&D cycle, from problem definition and research to implementation and productization with a high level of autonomy.
In addition, part of the role & responsibilities will be:
Design, develop and implement state-of-the-art Generative models, prompt engineering and classical ML/NLP techniques to create high-quality solutions for demanding product-oriented NLP tasks.
Engage in collaboration with product, account, and customer success teams to establish success criteria and convert them into measurable objectives and quantitative measures.
Conduct training and evaluation of models within practical production scenarios.

We are looking for a Data Operations Team Lead to lead and scale our data operations function. This role sits at the intersection of data, algorithms, and operations, and is critical to the success of our computer vision and AI models.
You will lead a distributed team responsible for data collection, annotation, quality control, and delivery, while working closely with Algorithm teams to understand model needs, prioritize requests, and ensure reliable, high-quality data pipelines.
This is a hands-on leadership role - you will manage people and processes, but also actively design, build, and improve data workflows.
About The Role
Lead and manage the Data Operations team, including annotation teams in Israel and a large remote team in India
Serve as the primary interface between Data Operations and Algorithm teams: understand model requirements, prioritize tasks, and plan data delivery
Own end-to-end data workflows, from model improvement needs through data definition, annotation guidelines, execution, and delivery
Ensure high data quality through close monitoring, validation, troubleshooting, and root-cause analysis
Design and maintain clear annotation guidelines, documentation, and training materials
Closely manage remote annotation teams, including weekly syncs, hands-on oversight, and deadline management
Own and operate the annotation pipeline using industry tools (e.g., CVAT)
Monitor progress, track performance, and continuously improve efficiency and quality
Own annotation budgets, monthly reporting, and validation of hours and outputs
Evaluate, benchmark, and implement new tools and processes in the data and annotation domain
Work hands-on with scripts, AI tools, and monitoring systems as needed to support data quality and operations.

It starts with you - ML Engineering Team Lead responsible for leading a team delivering end-to-end ML systems. This role combines people management with ownership of model training, evaluation, deployment, and ML platform standards
If you want to grow your skills building AI products for mission-critical AI, join our companys mission - this role is for you.
The Responsibilities
Lead and mentor ML Engineers delivering production ML systems.
Own technical direction for model architectures, training pipelines, and evals.
Review designs and code; ensure scalability, reliability, and data quality.
Define standards for experimentation, reproducibility, and monitoring.
Partner with product and platform teams on roadmap and prioritization.
Balance hands-on technical contribution with people management.
Build a culture of measurement, rigor, and continuous improvement.

It starts with you - a senior ML engineer responsible for building, training, evaluating, and operating machine learning systems in production. The role focuses on data pipelines, model training, experimentation, evaluation, and scalable deployment.
If you want to grow your skills building AI products for mission-critical AI, join our companys mission - this role is for you.
The Responsibilities
Design, train, and evaluate ML models for production use.
Build and maintain data pipelines for training, validation, and inference.
Own experimentation workflows: feature engineering, training runs, and comparison.
Implement model evals, monitoring, and drift detection.
Package and deploy models to production systems.
Optimize training and inference performance, cost, and reliability.
Collaborate with data, platform, and product teams.
Mentor engineers and promote ML engineering best practices.

At our company, we redefine cyber defense vision by combining AI and human expertise to create products that protect nations and critical infrastructure. This is more than a job; its a Dream job. we are where we tackle real-world challenges, redefine AI and security, and make the digital world safer. Lets build something extraordinary together.
our company'sAI cybersecurity platform applies a new, out-of-the-ordinary, multi-layered approach, covering endless and evolving security challenges across the entire infrastructure of the most critical and sensitive networks. Central to our company's proprietary Cyber Language Models are innovative technologies that provide contextual intelligence for the future of cybersecurity.
At our company, our talented team, driven by passion, expertise, and innovative minds, inspires us daily. We are not just dreamers, we are dream-makers.
The Responsibilities
Conduct cutting-edge research in natural language processing and large language models.
Design, train, and optimize large-scale neural network models for advanced applications.
Transition research projects from ideation through deployment and scaling.
Collaborate closely with cross-functional teams, including domain experts, product managers, and engineers, to deliver impactful AI solutions.
Define and contribute to the AI and NLP product roadmap.

We are looking for a Senior Machine Learning Algorithm Engineer who is passionate about solving complex, real-world problems at the intersection of hardware and software.
Location: Haifa \ Tel-Aviv in hybrid model.
Responsibilities
Develop advanced ML algorithms using data from our company Agents embedded in silicon. Example domains include:
Lifetime predictions
Clustering and dimensionality reduction
Parametric modeling and screening
Time-series forecasting
Lead end-to-end algorithm lifecycle: ideation → research → POC → design → implementation → validation → deployment.
Collaborate closely with cross-functional teams and directly with customers to continuously refine and enhance deployed solutions.
Drive integration of AI-enhanced tools and intelligent pipelines into ML workflows.