דרושים » תוכנה » Experienced Machine Learning Engineer

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 - Perception Solutions
Join our Perception Solutions team, working on significant computer vision challenges and solving them with cutting-edge neural networks combined with heuristic solutions.
In this role, you will join at the beginning of an end-to-end development cycle, leveraging advanced approaches to enable direct vision modeling beyond traditional image-processing pipelines and help advance the next generation of autonomous driving technology.
What will your job look like:
Contribute to building a new deep learning project from scratch, with real impact on production systems.
Work on end-to-end model development, including problem formulation, data understanding, model design, training, evaluation, optimization, and deployment.
Develop and train state-of-the-art deep learning models for computer vision tasks.
Explore and define the best technical approach in an open, research-driven environment, where solutions are not predefined.
Tackle real-world challenges where model performance is critical and directly impacts product capabilities.

Required Algorithm Researcher - Autonomous Driving (CTO Group)
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.

We are looking for an Expert Deep Learning Research Engineer who will both drive independent deep learning research and collaborate closely with other developers to help unlock new directions, solve complex challenges, and elevate the teams algorithmic capabilities.
What will your job look like:
Conduct hands-on research and development of deep learning algorithms for road understanding, drivable area detection, and scene structure modeling
Lead exploratory investigations into new architectures, training strategies, and data utilization methods
Join forces with other developers to troubleshoot difficult problems, introduce new ideas, and guide technical decisions
Own projects end-to-end - from concept and experimentation to integration and scalable deployment.

We are looking for someone who brings ML and computer-vision depth to the team - someone who can help shape the intelligence layer that decides what data is worth training on.
What will your job look like:
Work collaboratively with shared ownership. Your focus area will be the curation and ML side of our data pipeline, but you will contribute across the full stack alongside the rest of the team.
Build and improve the curation pipeline - from vision-model embeddings and scene detection, through VLM-based scene analysis, to scoring, deduplication, and sampling that produces a balanced and diverse dataset.
Run and optimize GPU inference at scale (embedding extraction, VLM inference) across thousands of driving sessions using workflow orchestration.
Develop scoring and sampling strategies that ensure rare but important scenarios (night driving, adverse weather, hazardous situations) are well-represented in the final dataset.
Work with algorithm teams to understand what data gaps hurt model performance and translate those into curation criteria.
Build validation and diagnostics that measure dataset quality - not just pipeline health, but whether the data is actually good for training.
Contribute to the core dataset SDK, converter, and 3D-geometry tooling (camera projection, calibration, coordinate transforms).

We are looking for a Deep Learning Tech Lead for Objects Modeling, who will be challenged by solving real-world problems using Computer Vision. Our mission in the algorithms department has a significant impact on autonomous vehicle technologies, external customers, and advanced driver-assistance systems (ADAS). In this role, you will be responsible for the full cycle of deep learning R&D, including modeling new solutions and enhancing the performance of existing ones. Your responsibility will include design, implementation, guidance and mentoring for team members. You will leverage your extensive experience to lead multiple deep projects, and will be a key figure in leading successful execution and in finding creative solutions to difficult bottlenecks, across data, AI, engineering and product considerations.
This role requires working at our Jerusalem offices 1 day per week.
What will your job look like:
Lead the design, development, and implementation of accurate and robust AI algorithms for new projects
Research the latest advancements in deep learning, multi-task learning, AI architectures, and apply them to enhance our algorithm
Design, develop and implement deep learning algorithms to solve complex problems in computer vision
Take ownership of deep learning projects: Design solutions, oversee execution, and collaborate with talented Algorithm developers
Collaborate with cross-functional teams to understand requirements and develop solutions.

Required Senior Data & ML Infrastructure Engineer
What will your job look like?
Optimize distributed data and evaluation pipelines for memory efficiency, throughput, and training performance.
Build tools for data exploration, manipulation, validation, and quality assessment.
Own model manipulation, packaging, distribution workflows, and interfaces with downstream deployment and EyeQ integration.
Coordinate data contracts and workflows with researchers, infrastructure and data teams, and internal customers across.

we are looking for a Senior ML Engineer.
Responsibilities:
Work on core data and machine learning infrastructure, which is at the heart of offering. You will create innovative solutions for data ingestion and normalization from multiple data sources, feature engineering and feature selection, as well as actual model training and evaluation. All in large scale and completely automated.

We are looking for a Senior Algorithm Engineer to lead the design and development of large scale ML inference and data processing systems in production. In this role, you will work at the intersection of algorithms, data systems, and machine learning infrastructure, building scalable and efficient solutions that support high throughput model inference and large scale data processing. The position involves close collaboration with ML researchers and infrastructure teams to design robust systems that power production ML workloads.
What will your job look like:
Design and optimize algorithms and pipelines for large scale model inference
Build scalable systems for high throughput data processing and streaming
Develop data transformation and preprocessing components for ML workloads
Improve performance, efficiency, and reliability across distributed inference systems
Work closely with ML researchers, infrastructure, and platform teams
Drive architectural decisions for production ML and data systems.

we are hiring a Software Engineer to help revolutionize the world of observability. Using cutting-edge AI-driven technology, we are redefining how organizations monitor, analyze, and optimize their systems-making observability more intelligent, efficient, and accessible than ever before. As we scale, we seek top talent to push the boundaries of innovation and shape the future of AI-powered observability. If you're passionate about solving complex challenges and building game-changing technology, join us in transforming how the world understands and interacts with data.



Responsibilities:

End-to-end development and ownership of products and features, from design to scalable and predictable production behavior

Solve diverse and complex problems in a high-scale, cloud-native environment

Collaborate with other engineers and product managers to improve product functionality, scalability, and performance

Design, develop, and maintain robust, secure, and efficient software solutions

Ensure high system reliability by implementing best practices in monitoring, observability, and automation

Review code, architecture, and data to identify and troubleshoot technical and performance issues

Work with AI/ML teams to integrate AI capabilities, including model monitoring, evaluation, and fine-tuning