לוח משרות דרושים Deep learning researcher משרה מלאה, לחיפוש זה נמצאו 22 משרות

We are now looking for a Solution Architect - Deep Learning based in Israel. The individual will collaborate with brand-new Agentic and Physical AI tools alongside Machine learning, Deep Learning, and Data analytics to improve workflows and develop groundbreaking solutions. We are widely considered to be one of the technology worlds most desirable employers. We have some of the most dedicated individuals in the world working for us. If you're creative and autonomous, we want to hear from you!

What You'll Be Doing:

Assisting field business development in guiding the customer through the sales process for GPU Computing products, owning the technical relationship and assisting the customer in building innovative solutions based on our technology.

Be a motivating leader in integrating our technology into HPC architectures to support scientific and engineering applications.

Be an internal champion for Deep Learning and Data Science among the technical community.

Develop demo solutions and showcase to the AI ecosystem.

We are the world leader in automotive and driving assistance systems, developing the world's most advanced software technologies and hardware architectures.
We are providing an end-to-end software solution for development and deploying features on its HW chip - EyeQ.
The compilers team is looking for a C++ Software engineer with a passion for low level optimizations and code analysis.
What will your job look like?
Develop and extend a compiler based on the LLVM infrastructure to support and optimize our EyeQ hardware.
Implement and improve middle‑end and back‑end compiler optimizations.
Analyze generated code to improve performance and efficiency.
Perform real-world benchmark analysis to find optimization opportunities.
Collaborate with chip architects on defining and supporting future hardware generations.

Required Senior Deep Learning Researcher
About the team:
A pioneering force in the autonomous vehicles (AV) industry.
Join us to build the brain behind the car - a large-scale, multi-task neural network that powers the core of our autonomous stack.
Youll design and train cutting-edge deep learning models tailored for our custom EyeQ chip, tackling end-to-end challenges and deploying real-world solutions.
From novel architectures and advanced training techniques to performance tuning under tight constraints, youll work closely with software and hardware teams to turn research into high-impact, production-ready systems.
If youre a brilliant, hands-on researcher with a passion for shaping the future - this is your launchpad.
Our team is at the forefront of our most advanced AI efforts. As a central hub for deep learning innovation, were trusted with designing the core neural network architecture that powers the companys flagship products. If youre seeking a high-impact role among top-tier researchers and developers - this is the place to be.

Required Outstanding Graduate - Machine Learning Engineer
About the team:
Our Hawkeye team is developing advanced close-range 3D perception for autonomous vehicles, enabling safe automated parking and low-speed maneuvers in tight environments. We build multi-camera deep learning systems for precise and reliable understanding of the vehicles surroundings.
What will your job look like:
Research and develop cutting-edge end-to-end 3D perception models combining geometry and semantics.
Work on 3D Semantic Occupancy, Geometry Reasoning, 3D Reconstruction, 3D Object Detection, and related tasks.
Innovate in multi-view fusion, motion handling, and spatial representation learning.
Deliver models that run on real vehicles and integrate into production systems.

Required Experienced Deep Learning Software Engineer - Algorithms & Data
About the team:
Our team develops models for road perception. We turn multi-sensor inputs (vision, maps, and more) into models that understand road geometry and behavior. We work at the intersection of algorithms, DL models, infrastructure, and data engineering.
what will your job look like?
Own road data pipelines end to end: tools for datasets and databases, running across S3 and on-prem
Design algorithms on large-scale vision and multi-sensor data (maps, sporadic inputs), including geometric reasoning from 2D image space to 3D world space for perception and world modeling
Implement and develop algorithms for the AV production system
Build evaluation tools, algorithms, metrics, and related infrastructures.

We are looking for an experienced Deep Learning Algorithm Developer to join one of our teams developing perception technologies for autonomous driving.
Our group tackles diverse challenges - from object detection and scene understanding to 3D perception - using large-scale, real-world in-house datasets and state-of-the-art deep learning models.
What will your job look like:
Develop and train neural networks for complex perception tasks in real-world driving environments.
Design and analyze deep learning pipelines, from data to deployment.
Collaborate with algorithm, software, and data experts to deliver production-ready models.
Research and apply new methods in computer vision, 3D perception, and multi-task learning to improve performance and efficiency.

Required Experienced Deep Learning Algorithm Developer
About the team:
The road algorithm team is responsible for the critical and challenging task of detecting the drivable lanes on the road. We focus on Deep Learning algorithms, classical Computer Vision and Geometric Modeling algorithms.
We are looking for an Algorithm Developer to help us advance our technology and push the boundaries of what's possible in autonomous driving.
What will your job look like:
Research and develop state-of-the-art computer vision and deep learning algorithms for ADAS and autonomous driving.
Participate in the entire development cycle, from initial research and prototyping to deployment on real-time embedded systems within the vehicle.
Collaborate with engineering and research teams in Computer Vision, Machine Learning, and Data Engineering to solve real-life problems.
Analyze large datasets to improve algorithm performance and robustness.

Required Deep Learning Researcher
About the team:
A pioneering force in the autonomous vehicles (AV) industry.
Join us to build the brain behind the car - a large-scale, multi-task neural network that powers the core of our autonomous stack.
Youll design and train cutting-edge deep learning models tailored for our custom EyeQ chip, tackling end-to-end challenges and deploying real-world solutions.
From novel architectures and advanced training techniques to performance tuning under tight constraints, youll work closely with software and hardware teams to turn research into high-impact, production-ready systems.
If youre a brilliant, hands-on researcher with a passion for shaping the future - this is your launchpad.
Our team is at the forefront of our most advanced AI efforts. As a central hub for deep learning innovation, were trusted with designing the core neural network architecture that powers the companys flagship products. If youre seeking a high-impact role among top-tier researchers and developers - this is the place to be.

Required Deep Learning Algorithm Engineer | Learned-Policy Group
About the team:
Build the intelligence behind the next driving decision.
Were developing learning-based driving policies for complex, real-world
scenarios. Were looking for an engineer who can turn model ideas into reliable
algorithms that run as part of our driving systems.
Youll work across model development, training, evaluation, and integration.
Youll analyze model behavior, improve the data and training process, and work
with other teams to validate performance in simulation and on real vehicles.
This is a high-impact role with direct influence on a core part of our
driving technology and its future products.
What will your job look like?
Develop and improve deep learning models for planning, decision making, and driving behavior.
Work across the full development cycle, from research papers and
prototyping models to building data and evaluation tools, debugging
infrastructure, and supporting deployment.
Design training and evaluation workflows, including metrics for safety,
progress, comfort, interaction quality, and robustness.
Analyze model behavior and failure modes, run experiments, and use the results to improve models and data.
Collaborate with control, simulation, data, and other algorithm
teams to integrate and validate new capabilities.

The road algorithm team is responsible for the critical and challenging task of detecting the drivable lanes on the road. We focus on Deep Learning algorithms, classical Computer Vision and Geometric Modeling algorithms.
We are looking for an Algorithm Developer to help us advance our technology and push the boundaries of what's possible in autonomous driving.
What will your job look like:
Develop and optimize computer vision and deep learning algorithms to accelerate data generation and labeling workflows for autonomous driving
Apply both classical computer vision techniques and modern deep learning methods to solve large-scale data challenges
Collaborate closely with development and annotation teams to enhance automation and ensure high-quality data
Own the entire lifecycle from prototyping to scalable deployment within internal pipelines and tools
Develop tools to evaluate and analyze algorithm performance, robustness, and operational efficiency.

Required Algorithm Researcher - Autonomous Driving (CTO Group)
About the team:
The CTO Group is a small, elite team focused on the decision-making module of our autonomous driving system.
Our mission is to solve some of the hardest problems in autonomous driving by combining the full spectrum of modern computer science - from rigorous mathematical modeling, optimization, and algorithm design to deep learning.
The team develops the driving policies that translate system-wide inputs into safe, efficient, and human-like driving behavior. Our work spans classical algorithms, optimization under constraints, probabilistic reasoning, reinforcement & supervised learning, all grounded in real-world driving data.
The group is comprised of top researchers and developers and is led by world-class scientists, offering a unique opportunity to work closely with the CTO, shape the future of autonomous driving, and influence the company's technical direction.
What will your job look like:
Research and develop innovative algorithms for autonomous driving planning and decision-making.
Model complex real-world driving scenarios and formulate them as optimization, learning, or algorithmic problems.
Apply a broad range of techniques - from mathematical modeling and classical algorithms to machine learning and deep learning - to improve driving policies.
Analyze large-scale driving data to gain insights, validate hypotheses, and improve system robustness and performance.
Design and implement high-quality production-ready code in a research-driven environment.
Read, evaluate, and build upon state-of-the-art scientific literature in algorithms, AI, and machine learning.

Required Reinforcement Learning Researcher | Learned-Policy Group
About the team:
What will your job look like?
Research and develop reinforcement-learning planning algorithms, including policy architectures, reward design, training objectives, and optimization methods.
Train and evaluate RL policies for difficult, interactive driving scenarios,
building on the existing learning-based planner and complementary classical components.
Develop evaluation methods and relevant metrics for safety, progress, comfort, and interaction quality, and use them to guide experiments and analyze failures.
Build simulation-based training and closed-loop evaluation workflows.
Turn research ideas into reliable components of the driving stack.

We are looking for an experienced Deep Learning Algorithm Developer to join one of our teams developing perception technologies for autonomous driving.
Our group tackles diverse challenges - from object detection and scene understanding to 3D perception - using large-scale, real-world in-house datasets and state-of-the-art deep learning models.
What will your job look like:
Develop and train neural networks for complex perception tasks in real-world driving environments.
Design and analyze deep learning pipelines, from data to deployment.
Collaborate with algorithm, software, and data experts to deliver production-ready models.
Research and apply new methods in computer vision, 3D perception, and multi-task learning to improve performance and efficiency.

We are looking for an Algorithm Developer to help us advance our technology and push the boundaries of what's possible in autonomous driving.
What will your job look like:
Research and develop state-of-the-art computer vision and deep learning algorithms for ADAS and autonomous driving.
Participate in the entire development cycle, from initial research and prototyping to deployment on real-time embedded systems within the vehicle.
Collaborate with engineering and research teams in Computer Vision, Machine Learning, and Data Engineering to solve real-life problems.
Analyze large datasets to improve algorithm performance and robustness.

Required Deep Learning Algorithm Engineer - REM Semantics
About the team:
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.
You will be joining the team that builds the state-of-the-art AI-powered relevancy systems at scale. You will be designing and implementing semantic understanding engines that power data-driven products across autonomous driving and beyond, combining cutting-edge Computer Vision, Graph Neural Networks, and efficient inference to solve real-world perception challenges.
What will your job look like:
Conduct hands-on research and development of AI and Deep Learning algorithms for real-world automotive perception tasks.
Own projects end-to-end - from concept, through research, prototyping, designing, training, and evaluating neural network architectures, to integration and scalable deployment.
Analyze challenging edge cases and continuously improve model performance in complex driving scenarios.
Collaborate with algorithm developers, software engineers, product managers and system teams across the organization.
Work with large-scale datasets and real-world driving scenarios to improve model accuracy, robustness, and runtime efficiency.
Bring your ideas into production-ready systems that have a direct, measurable impact on autonomous vehicle technologies used worldwide.