דרושים » AI » AI Python Developer

In this role, you will build deep expertise in AI fundamentals, LLM and generative AI network architectures, and their underlying algorithms. You will continuously research emerging generative AI architectures across the industry, staying ahead of how the field evolves.
A central focus will be quantization - understanding, developing, and refining quantization methods and algorithms, and driving their deployment on our hardware to achieve maximum performance without compromising accuracy.
Responsibilities:
Explore and plan end to end network deployment on our company's hardware.
Own network accuracy measurement and improvement.
Develop the graph compiler's hardware-aware quantization tool.

As a Senior AI Engineer in the MSC IL AI Innovation team, you will lead the design, development, and productization of advanced AI solutions for our Specialized Clouds, with a strong focus on sovereign-first, secure, and responsible AI systems.

You will operate as a technical leader, owning end‑to‑end AI architecture and delivery, influencing platform direction, and mentoring engineers while working closely with architects, product managers, security, and operations teams. This role goes beyond implementation; you will shape how AI is built, governed, and scaled across sovereign and regulated cloud environments.


Responsibilities

Design and build AI agents that plan, use tools/APIs, manage state/memory, and reliably complete multi-step workflows.

Own AI features from design through production, including deployment, monitoring, and live‑site reliability, with an eval-first development lifecycle: define success criteria, build evaluation datasets and automated harnesses, and run human-in-the-loop reviews where needed.

Develop and maintain prompt, retrieval, and memory strategies (system prompts, few-shot examples, tool schemas, retrieval context) with proper versioning and evaluation coverage.

Debug AI behavior using prompt analysis, data inspection, and model/tool-call traces, and translate failure patterns into targeted improvements.

Establish and track AI quality metrics (e.g., accuracy, groundedness, relevance, hallucination rate) and integrate them into CI/CD release gates.

Optimize runtime performance and economics (token usage, inference cost, latency, caching, model selection/routing, batching) and implement monitoring and continuous improvement loops (online signals, drift detection, structured user feedback).

Partner with product, design, and domain stakeholders to define use cases, acceptance criteria, and rollout plans for AI features.

Live site responsibility.

In this role, you will learn and deeply understand the AI fundamentals and create tools that simulate our companys AI neural network processor implementation.
In addition, you will perform in-depth analysis and optimization to the simulator, to ensure simulator performance and accuracy for various companys processors architectures.
The project is using C/C++ OOP as main development language as well as python for AI neural network.
Development platforms are Linux and Windows based.
Responsibilities:
Taking part of innovative, agile, top-notch Software organization, designing Neural Network Processor (NPU) simulator in close collaboration with the architecture, algorithms, system and hardware teams.
Design and develop simulation software solutions allowing our company customers to run most advanced AI networks efficiently on our company NPU software simulation.

Required AI Engineer
As an AI Engineer, you will:
Play a central role in advancing AI capabilities across the company and turning emerging AI technologies into practical, production-ready solutions
Research and evaluate new AI technologies, identify valuable use cases and develop solutions that improve internal workflows, existing products and enable new AI-powered capabilities
Lead AI solutions end to end, from research and proof of concept to design, development and production
Collaborate closely with development, product and business teams to integrate AI models, agents, data and reusable AI services into existing systems
Design and develop RAG, knowledge systems, AI agents and multi-agent workflows
Evaluate and benchmark AI models and solutions, balancing quality, accuracy, latency, throughput and cost
Find creative and practical solutions to complex technical and business challenges and help expand the companys internal AI ecosystem

Required Research Engineer, Generative Media, DeepMind
About the job
Our team's mission is to build frontier generative media experiences. We are pushing the boundaries of what is possible by developing real-time, interactive video models like Genie, as well as exciting new applications and capabilities.
We have a proven track record of researching and delivering foundational generative models for video and action-controllable virtual worlds, as well as applications such as video stylization, reference-to-video generation, and precise object insertion and removal.
Artificial intelligence will be one of humanitys most transformative inventions. At DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.

We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.
Responsibilities
Design, implement, train, and evaluate novel deep learning models for real-time generative media, including video-audio synthesis, manipulation, and understanding.
Develop and optimize algorithms and systems for AI experiences on Omni platforms, focusing on live dialog, live video editing, and crosscut.
Collaborate with research scientists and engineers to prototype, experiment, and scale generative AI techniques using software engineering best practices.
Contribute to the design of datasets, evaluation methodologies, and infrastructure required for training and testing generative models.
Analyze results to iterate on architectures, contribute to research publications, and help deploy successful research into GDM and our products.

In this role, as Embedded Software Team Leader, you will lead a team owning a key part of our company's NPU AI software stack, a complex, multi-layered system spanning the Host (SDK, runtime, APIs, and UMD/KMD drivers) and the NPU IP (embedded firmware). This stack is at the heart of the company AI software offering, with deep impact on multiple hardware and software teams ability to execute state of the art LLM, Generative AI and Neural Networks with extraordinary performance. Reporting to the AI Software SDK Senior Team Leader, you will lead a team of creative and result oriented enthusiasts that invent, design, and implement software that enables smooth connectivity between the NPU and Host CPU.
Responsibilities:
Lead and manage the Embedded Software engineering team, ensuring high performance and productivity.
Own the design, development, and implementation of your component within our company's NPU AI software stack, aligned with the AI Software SDK group's technical strategy, architecture, and roadmap and its automated CI and release process.
Collaborate with cross-functional teams to integrate solutions. Provide technical guidance and mentorship to team members.
Ensure project timelines and deliverables are met.
Conduct performance reviews and support professional development of team members.
Collaborate globally with architects, HW teams, NPU teams, and other developer teams.

Required Research Engineer, Generative Media
About the job
Research-focused Software Engineers are embedded throughout the company, allowing them to setup large-scale tests and deploy promising ideas quickly and broadly. Ideas may come from internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world.
From creating experiments and prototyping implementations to designing new architectures, engineers work on real-world problems including artificial intelligence, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more. But you stay connected to your research roots as an active contributor to the wider research community by partnering with universities and publishing papers.
The Creative Camera team mission is to imagine and build the future of photography and videography. Our team is reinventing digital imagery: from pioneering new generative and diffusion models for creating the highest-quality images and videos possible, to creating entirely new ways of capturing and reliving our experiences.
The Platforms and Devices team encompasses our various computing software platforms across environments (desktop, mobile, applications), as well as our first party devices and services that combine the best of AI, software, and hardware. Teams across this area research, design, and develop new technologies to make our user's interaction with computing faster and more seamless, building innovative experiences for our users around the world.
Responsibilities
Design, implement, train, and evaluate deep learning architectures-particularly diffusion models and transformers-for image and video synthesis.
Develop and apply algorithms in computer vision, graphics, and machine learning for our applications, focusing on computational photography, computational videography, and content creation.
Conduct both fundamental and applied research to identify and solve creative, novel problems that revolutionize editing, and creation of visual media.
Leverage deep theoretical and practical knowledge to prototype new technologies that unlock visual experiences for users.
Build upon our strong track record of publishing graphics venues (with previous publications including Dreambooth, GameNGen, ObjectMate, LightLab, and many more), and successfully transfer these innovations into our products that reach millions to billions of users.

we are looking for a AI Engineer.
Our R&D teams build and own the features that power platform - from deep code analysis to risk detection to developer-facing workflows. AI isn't a separate initiative here; it's how we build. Every engineering team is actively embedding LLMs, AI agents, and generative AI into the products they own, moving from experimentation to production and keeping things running reliably once they're there.
What You Will Do
Build and ship end-to-end AI-driven features and agentic workflows- from experimentation through validation to production deployment (Python and C#).
Design scalable backend services that support production-grade agentic AI capabilities.
Develop and improve solutions powered by LLMs, AI agents, multi-agent systems, and generative AI frameworks.
Evaluate agentic architectures and model performance, owning monitoring, reliability, and continuous improvement in production.
Collaborate cross-functionally with software engineers, data scientists, and analysts to drive AI innovation across the platform.