דרושים » תוכנה » Senior Computer Vision Data Engineer

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're looking for a Data Engineer with 4+ year experience to join our Data Engineering team and help us build and scale our production-grade data platform. You'll work on high-performance systems built on self-hosted ClickHouse, optimize complex data pipelines, and collaborate closely with Product, Analytics, and Infrastructure teams to deliver reliable, fast, and scalable data solutions.
This is a hands-on technical role where you'll have a significant impact on how we ingest, model, store, and serve data that powers our analytics and AI-driven products.
Youll play a key role in shaping the direction of our data platform and have meaningful ownership over critical components of our architecture.

We're looking for an Applied Data Scientist to own the data science strategy behind this initiative.
This is a high-ownership, senior role sitting at the intersection of product, data science, and capital markets. You'll build statistical and ML models end to end - from conception through production - and turn complex financial-product questions into reliable, customer-facing decisioning systems. You'll work across Product, Engineering, Finance, Operations, Legal, and external capital partners to define how evaluates financial-product opportunities, manages risk, measures performance, and scales responsibly.
The right person brings strong modeling depth, sharp product judgment, and the business context to work in ambiguity. Fintech, lending, credit, or risk experience is strongly preferred - but we're also open to senior data scientists from adjacent domains who've built high-stakes models in complex, data-rich environments.
What Youll Do:
Own the end-to-end data science strategy for financial products - from roadmap and model development to production deployment and governance.
Build models and decisioning frameworks across the full lending lifecycle: merchant eligibility, underwriting, risk assessment, repayment behavior, and growth forecasting.
Translate ecommerce, revenue, marketing, and operational data into actionable signals that power financial-product decisions and partner evaluations.
Partner with Product, Engineering, Finance, Legal, and Operations to turn analytical work into scalable data products, APIs, internal tools, and explainable recommendations that hold up in commercial and regulatory contexts.
Design measurement frameworks that span funnel performance, repayment outcomes, customer adoption, partner performance, and long-term unit economics.
Establish model validation, monitoring, and governance practices appropriate for high-stakes financial decisioning.
Define the long-term fintech data science roadmap - what to build internally, what to partner on, and where modeling can create durable competitive advantages.

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 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 offers the flexibility to work part-time from our other sites, subject to seat availability.
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.

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 a Research Scientist .
As a Large Scale Video Understanding Research Scientist, you will play a key role in improving video generation quality and efficiency by improving video and audio understanding pipelines used for both training data construction and model evaluation.. This role demands hands-on work with large-scale Video Language Models (VLLMs), including fine-tuning, post-training, and control, alongside implementing classic computer vision and signal processing algorithms and applying strong research skills. Your expertise in post-training and controlling large scale foundational models, understanding statistics, implementing complex systems and eliminating bugs will be crucial, as our video training sets consist of petabytes of data processed across hundreds to thousands of virtual machines.
What you will be doing:
Fine-tune and control VLLMs for video and audio understanding.
Design algorithms for balancing, filtering, and curating training and evaluation datasets, informed by model behavior and failure modes.
Implement classic and modern algorithms for processing, clustering, evaluation and filtering of large scale datasets.
Work within high-performance, scalable distributed systems capable of handling petabytes of data, with attention to throughput, correctness, and reproducibility..
Collaborate with other researchers and product stakeholders to iteratively improve training sets and evaluation protocols through tight feedback loops driven by model performance.

We are looking for an MLOps Software developer to help us design and implement our large-scale platform using the most up-to-date technologies.
What will your job look like:
Collaborate with algorithm developers to research, develop, and deploy machine learning models at a large scale.
Leverage our data sources and cloud computing to build an infrastructure that process terabytes of data to improve our machine learning models.
Perform software research, development, evaluation, and optimization.
Design and implement large scale systems.