What will your job look like: Lead end-to-end development of features - from design and implementation to integration, testing, and deployment Build ML pipelines for data-based diverse dataset creation and efficient model inference Design data selection and sampling strategies to ensure coverage of rare and critical scenarios Partner with algorithm teams to translate model weaknesses into data curation criteria Develop validation and diagnostics to measure dataset quality—not just pipeline health but training effectiveness Integrate neural network models into C++ production systems, including runtime, data flow, and pre/post‑processing Bring models from research/prototype stage into robust, production‑ready deployments Optimize runtime performance (latency, memory, and throughput) in resource‑constrained environments Contribute to deployment flows (e.g., model conversion, profiling, optimization) Build and improve CI/CD pipelines, automated testing, and development workflows All you need is: B.Sc. in Computer Science, Software Engineering, or equivalent 3+ years of hands-on C++ development experience 3+ years of hands-on Python development experience, including the PyData stack (NumPy, Pandas) Experience working in Linux environments Strong motivation to work closely with deep learning algorithms and production of AI systems Interest in neural network deployment on edge devices, including inference runtimes, performance optimization, and model integration Proven ability to work across team boundaries (algorithms, infra, product) Strong motivation to work on production AI systems and deep learning integration Interest in edge deployment, inference runtimes, and performance optimization Advantages: Experience with autonomous-driving datasets or perception pipelines Background in 3D geometry and/or strong mathematical foundation Experience with workflow orchestration tools (Airflow, Argo) Familiarity with data curation techniques (e.g., active learning, hard example mining, distribution balancing) 2+ years in data engineering or backend systems with large‑scale data (production environments)
