ML Software Engineer

we are seeking a strong ML Software Engineer to join our deep learning LiDAR & Radar group and help scale the systems that bring cutting‑edge perception models into production. Youll build the software layers, data pipelines, and runtime systems that turn advanced neural networks into reliable, high-performance solutions running on edge devices.This is a hands-on, high‑ownership role within a growing group working closely with algorithm developers. The work spans Python and C , ML infrastructure, model integration, performance optimization, and production delivery.What will your job look like:Lead end-to-end development of features - from design and implementation to integration, testing, and deploymentBuild ML pipelines for data-based diverse dataset creation and efficient model inferenceDesign data selection and sampling strategies to ensure coverage of rare and critical scenariosPartner with algorithm teams to translate model weaknesses into data curation criteriaDevelop validation and diagnostics to measure dataset quality-not just pipeline health but training effectivenessIntegrate neural network models into C production systems, including runtime, data flow, and pre/post‑processingBring models from research/prototype stage into robust, production‑ready deploymentsOptimize runtime performance (latency, memory, and throughput) in resource‑constrained environmentsContribute to deployment flows (e.g., model conversion, profiling, optimization)Build and improve CI/CD pipelines, automated testing, and development workflows.Requirements: B.Sc. in Computer Science, Software Engineering, or equivalent3 years of hands-on C development experience3 years of hands-on Python development experience, including the PyData stack (NumPy, Pandas)Experience working in Linux environmentsStrong motivation to work closely with deep learning algorithms and production of AI systemsInterest in neural network deployment on edge devices, including inference runtimes, performance optimization, and model integrationProven ability to work across team boundaries (algorithms, infra, product)Strong motivation to work on production AI systems and deep learning integrationInterest in edge deployment, inference runtimes, and performance optimizationAdvantages:Experience with autonomous-driving datasets or perception pipelinesBackground in 3D geometry and/or strong mathematical foundationExperience 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).This position is open to all candidates.