Machine Learning Engineer: Perception and Planning

United States·OaklandFull Timemid

Data ScienceMachine Learning EngineerDataMachine LearningData & AI

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BlueSpace.ai is revolutionizing the autonomous vehicle industry with our groundbreaking self-driving technology. Unlike conventional autonomy software, our patented 4D Predictive Perception removes reliance on data. By leveraging next-gen 4D sensors, we can precisely predict the motion of all objects, increasing accuracy, lowering latency, and setting a new standard for safety and efficiency in autonomy.

Our team consists of seasoned professionals from across the autonomous vehicle (AV) ecosystem, including OEMs, world-class research institutions, and leading autonomous driving companies. With a proven track record of successful AV service launches in California, Texas, and Florida, we are well-positioned to drive the next generation of autonomy.

We are seeking talented, self-motivated individuals who thrive in a fast-paced, dynamic environment and are passionate about making a significant impact on the future of mobility. If you’re driven to tackle the most complex challenges in autonomy and push the boundaries of what is possible, we want to hear from you.

Develop deep learning models for a variety of autonomy applications (relevant areas: object detection, classification, segmentation, behavior prediction, end-to-end driving).

Research, design, improve, and implement state-of-the-art ML algorithms and deploy them onto self-driving vehicles and in datacenters.

Identify or collect the required datasets and implement data processing pipelines.

Deliver reliable software through continuous integration, automated testing, and code reviews.

Address the real-world issues encountered during tests or customer deployments.

Bachelor’s Degree in Computer Science, Mechanical Engineering, Electrical Engineering, or equivalent. Advanced Degrees highly preferred.

Demonstrated ML Engineering experience developing either Computer Vision models (preferred) or other models (such as LLMs, Finance, Ads, or others).

Production experience with Deep Learning models (training, fine-tuning, or deployment).

Excellent software engineering skills in Python or C++.

Strong analytical skills in linear algebra, geometry, and probability.

Experience with a deep learning framework, such as PyTorch, JAX, TensorFlow.

Relevant industry experience with low-latency systems (prior work on self-driving vehicles, autonomy, and/or robotics projects).

Experience building models from sensor data: lidar, radar, camera.

Experience with multi-modal models.

Strong academic track record in any field related to machine learning, as evidenced by top-tier publications.

Production ML experience with either: Model conversion and optimization for production (ONNX, TensorRT); Model deployment on specialized hardware (e.g. Jetson).

Ability to lead the ML area as the team grows (for Sr Staff level candidates)