BlueSpace.ai is building the next generation of self-driving technology to create the safety certainty needed for genuinely driverless vehicles. Our patented 4D Predictive Perception enables this by calculating all objects’ motion from next-gen 4D sensors.
BlueSpace.ai’s team brings experience from all over the autonomous vehicles (AV) industry, including OEMs, world-class research institutions, and autonomous driving companies.
We welcome self-driven individuals who excel under limited direction to join our award-winning team and company.
As the ML Infrastructure Engineer at Bluespace, your mission will be to develop the Cloud Data Infrastructure System to support and enable our Assured AI for Autonomy.
You will have the opportunity to design and develop the infrastructure, which will allow our developers to expand Bluespace’s APNT capabilities.
Duties and Responsibilities
- Take ownership of the infrastructure in support of developing and deploying Machine Learning models for Autonomous Vehicles
- Architect and deploy cloud and on-prem ML training and evaluation infrastructure
- Own the the data management pipelines, from ingestion and storage, to model training and evaluation that span vehicle compute, cloud, and on-prem
- Change model training code to take advantage of the better data storage techniques and formats you propose
- Evaluate and implement methods, software, and hardware for model deployment onto the test and production vehicles
- Develop systems and processes to improve transition of models from research to production while balancing cost
- Participate in model design, research and set requirements to model design that ensure their successful deployment
- Own and deliver projects end-to-end
- Optional: be able to hire, manage, or at least mentor other engineers who join this project when growth is needed
Qualifications and Experience
- Experience in architecting and implementing data engineering solutions for a small engineering team / product (1-20 ppl)
- 2+ years of software engineering experience in any of the following: ML Infrastructure, Data Engineering, Platform Engineering, Distributed Systems
- Either existing experience with ML Infrastructure as described below, or strong expertise in non-ML Data infrastructure combined with a strong desire to learn ML Infra specifics
- Production ML experience with at least one of the following - (1). Model conversion and optimization for production (ONNX, TensorRT), (2) Model deployment on specialized hardware (e.g. Jetson), or (3) Model monitoring and MLOps
- Ability to programmatically access cloud services using Python, NodeJS, or equivalent
- Knowledge of or experience with data management solutions, such as - (1) Workflow orchestration pipelines (e.g. Argo, Airflow, Kubernetes) or (2) Managed large-scale data processing systems (e.g. Spark, Dataproc, Databricks)
- End-to-end ML pipelines (e.g. SageMaker, Vertex)
Extra Credit
- Experience with Terraform or a similar IAC solution
- Robotics background, C++, ROS
- Experience with Google Cloud Platform or other major cloud provider
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.
