Develop deep learning models for autonomy applications, implement ML algorithms for self-driving vehicles, and resolve real-world testing issues.
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.
Duties and Responsibilities
- 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.
Qualification and Experience
- 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.
Extra Credit
- 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)
BlueSpace.aI is an Equal Opportunity Employer. Qualified applicants will receive consideration for employment without regard to race, color, gender, religion, sex, sexual orientation, age, disability, military status, or national origin or any other characteristic protected under federal, state, or applicable local law.
BlueSpace.ai Emeryville, California, USA Office
Emeryville, California, United States
Similar Jobs
Artificial Intelligence • Cloud • Machine Learning • Mobile • Software • Virtual Reality • App development
Lead and mentor a mobile client media platform engineering team responsible for end-to-end media infrastructure (recording, transcoding, upload, storage, CDN, streaming, playback). Set strategy and roadmap, collaborate cross-functionally, evaluate technical tradeoffs, hire and retain talent, and use AI tools and high-velocity workflows to deliver scalable, secure, production-ready systems.
Top Skills:
Ai ToolsCdnDistributed SystemsMedia ManagementReplicationStorageStreamingTranscodingVideo PlaybackVideo PlayerWeb Development
.png)
eCommerce • Fintech • Hardware • Payments • Software • Financial Services
Field-driven Territory Account Executive responsible for full-cycle sales: prospecting, live demos, closing deals, building pipeline via door-to-door outreach and partnerships, driving 50–60 weekly visits, managing Salesforce, and exceeding quota while supporting seller onboarding and time-to-value.
Top Skills:
AfterpaySalesforceSquare
Artificial Intelligence • Cloud • Security • Software • Cybersecurity
Lead and scale strategic ISV go-to-market partnerships globally by aligning with Product, developing and executing GTM plans, driving joint revenue opportunities, enabling field and partner sales, creating marketplace listings, and measuring partnership performance to optimize impact.
Top Skills:
AICloud MarketplacesCloud TechnologiesDatadogSecurity
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
