דרושים » AI » AI /ML & data Integration Engineer

We are looking for a deep learning algorithm developer to join our growing team under our companys Algorithms Group. The team is building an innovative multimodal learning framework aimed at improving autonomous driving performance by understanding long-tail cases and providing actionable navigation insights. Were combining state-of-the-art vision-language models to revolutionize how we train, validate, and scale our autonomous systems. If youre passionate about deep learning and engineering high-impact autonomous solutions - this is the place for you.
What will your job look like:
Contribute to dataset curation activities - collecting, cleaning, labeling, and preparing multimodal data for training and validation.
Train and fine-tune LLMs, VLMs, and VLA models to interpret visual scenes and produce actionable navigation insights supporting autonomous vehicle decision-making.
Support validation of multimodal models - evaluating vision-language-action behavior and helping identify performance gaps across driving scenarios.
Collaborate closely with AV planners, perception teams, and infrastructure engineers to ensure seamless deployment in a real-time ecosystem.
Youll have the opportunity to influence the strategic direction of language-driven autonomy - proposing new ideas, shaping model capabilities, and driving innovation from research to real-world deployment.

Our team at the Huawei Computing Network Innovation Lab is looking for exceptional talent to join us and lead the development of next generation data centers. We create cutting-edge technologies that synergize software and hardware in tandem to accelerate compute, storage and networking at large-scale. We aim to drive innovations and deliver software defined infrastructure and algorithms to HPC, AI/ML, and Big Data applications.
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 looking for an exceptional deep learning algorithm developer with proven experience in LLMs/VLMs/VLA models to join our growing team under our copmpanys Algorithms Group. The team is building an innovative multimodal learning framework aimed at improving autonomous driving performance by understanding long-tail cases and providing actionable navigation insights. Were combining state-of-the-art vision-language models to revolutionize how we train, validate, and scale our autonomous systems. If youre passionate about deep learning and engineering high-impact autonomous solutions - this is the place for you.
What will your job look like:
Lead dataset curation strategy - designing scalable pipelines for multimodal data to drive high-quality training and validation.
Architect and optimize LLMs, VLMs, and VLA models - transforming scene understanding into reliable driving guidance.
Own the validation strategy - defining methodologies, metrics, and failure-analysis workflows for robust vision-language-action alignment.
Make an immediate impact by applying deep expertise to guide model design, methodology, and development priorities from day one.
Collaborate closely with AV planners, perception teams, and infrastructure engineers to ensure seamless deployment in a real-time ecosystem.
Influence the technical direction of language-driven autonomy - contributing experience, shaping capabilities, and driving innovation to production.

We are looking for a senior deep learning algorithm developer to join our growing team under our companys Algorithms Group. The team is building an innovative multimodal learning framework aimed at improving autonomous driving performance by understanding long-tail cases and providing actionable navigation insights. Were combining state-of-the-art vision-language models to revolutionize how we train, validate, and scale our autonomous systems. If youre passionate about deep learning and engineering high-impact autonomous solutions - this is the place for you.
What will your job look like:
Own dataset curation activities- acquiring, cleaning, labeling, and tailoring multimodal data to meet model training and validation requirements.
Train and fine-tune LLMs, VLMs, and VLA models to interpret visual scenes and produce actionable navigation insights supporting autonomous vehicle decision-making.
Lead robust validation of advanced multimodal models - ensuring reliable vision-language-action alignment and consistent performance across diverse real-world driving scenarios.
Collaborate closely with AV planners, perception teams, and infrastructure engineers to ensure seamless deployment in a real-time ecosystem.
Youll have the opportunity to influence the strategic direction of language-driven autonomy - proposing new ideas, shaping model capabilities, and driving innovation from research to real-world deployment.

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.