דרושים » הנדסה » Applied ML control engineer

We are seeking a capable and experienced Algorithm engineer to join our R&D team. The engineer will be part of a team responsible for the core autonomy parts of the product responsible for developing the foundational algorithms that guide our autonomous vehicles. This role is a part of the group that oversees Motion Planning, Decision-Making, Localization, and Control, blending traditional robotics with state-of-the-art AI to solve the most challenging problems in autonomous driving. This is an opportunity to architect and deliver the core autonomy stack for a scalable, mapless L3-L4 system. You will work on cutting-edge algorithms, including Agentic AI and large-scale models, and see your innovations deployed on public roads in our global fleet of cars and buses. Responsibilities
* Be part of the development of four key domains: Motion Planning and Decision-Making: Oversee the trajectory planner and the decision-making module that sets the context for vehicle behavior. Localization: Guide the development of high-frequency, high-accuracy vehicle state estimation using advanced sensor fusion algorithms. Control: Supervise the design and implementation of the vehicle's lateral and longitudinal controllers.
* Drive innovation by integrating state-of-the-art (SOTA) methodologies, including Agentic AI, vision language models (VLMs), transformers, multi-agent prediction, trajectory optimization, uncertainty management, and safety-aware algorithms.
* Be part of a group involving multiple engineers, from initial research and prototyping to robust deployment and validation.
* Be part of a group in charge of complex data pipelines, from collection and annotation to model training and evaluation.

We are seeking a motivated and skilled Jr. Algorithm Engineer to join our R&D team. The engineer will be part of a team responsible for the core autonomy parts of the product responsible for developing the foundational algorithms that guide our autonomous vehicles. This role is a part of the group that oversees Motion Planning, Decision-Making, Localization, and Control, blending traditional robotics with state-of-the-art AI to solve the most challenging problems in autonomous driving. This is an opportunity to architect and deliver the core autonomy stack for a scalable, mapless L3-L4 system. You will work on cutting-edge algorithms, large-scale models, and see your innovations deployed on public roads in our global fleet of cars and buses. Responsibilities
* Be part of the development of four key domains: Motion Planning and Decision-Making: Oversee the trajectory planner and the decision-making module that sets the context for vehicle behavior. Localization: Guide the development of high-frequency, high-accuracy vehicle state estimation using advanced sensor fusion algorithms. Control: Supervise the design and implementation of the vehicle's lateral and longitudinal controllers.
* Drive innovation by integrating state-of-the-art (SOTA) methodologies, including Agentic AI, transformers, multi-agent prediction, trajectory optimization, uncertainty management, and safety-aware algorithms.
* Be part of a group involving multiple engineers, from initial research and prototyping to robust deployment and validation.
* Be part of a group in charge of complex data pipelines, from collection and annotation to model training and evaluation.

We are looking for outstanding candidates with hands-on experience in development and optimization of AI frameworks. If you are a team player with excellent communication skills and motivation to revolutionize application performance, youre welcome on board!
What will you be doing?
Work as part of an innovative research team to analyze, develop, test and deploy improvements that enhance Huaweis distributed AI framework.
Develop optimizations that leverage hardware accelerator capabilities, minimize communication overhead and improve training/inference throughput
Push the boundaries of the state of the art in LLM performance and efficiency, including model compression and quantization
Analyze, profile and optimize the latest LLM AI algorithms, and implement as production-quality software libraries for latency-critical use-cases on next-generation hardware.
Work in a distributed computing environment to optimize for both scale-up (multi-device) and scale-out (multi-node) systems
Utilize advanced concepts such as Uncertainty Quantification, Mixed Precision Computing and Model Sparsity to improve performance and enable training of very large AI models
Collaborate with partners from top universities, and open-source communities to conduct state-of-the-art research

We are recruiting an MLOps / AI-Ops Engineer to join our data & AI Division in Haifa.
This role is responsible for managing, optimizing, and scaling the organizations AI/ML infrastructure across both cloud and on-prem environments, ensuring high availability, performance, and cost efficiency.
Role Overview:
* Manage day-to-day AI infrastructure operations, ensuring reliability, performance, and scalability.
* Deploy, configure, maintain, and troubleshoot AI platforms and tools, including GPU orchestration, Kubernetes, MLflow/Kubeflow, and vector databases.
* Monitor resource utilization (CPU, GPU, memory, Storage, network) and implement performance optimizations.
* Support CI/CD pipelines and infrastructure automation using Infrastructure as Code (Terraform, Ansible).
* Implement security best practices, manage access control, and ensure compliance with AI governance policies.
* Troubleshoot operational incidents and collaborate with AI Platform and AI Security Engineers.
* Contribute to documentation, runbooks, and knowledge sharing.
* Identify opportunities to improve AI infrastructure processes and tooling.