Mission Summary:

We are seeking an experienced and visionary Staff Engineer to technically anchor our new AI Data Engine team. This pivotal role will drive the technical strategy, architecture, and execution of initiatives aimed at significantly accelerating our ML dataset generation and our data warehouse stack. The ultimate goal is to drastically reduce the development cycle for new pipelines, ML models and get us operationally prepared for a driverless future!

You will be a hands-on technical leader, blending deep expertise in data systems and infrastructure with the ability to architect complex, highly scalable solutions. While this is an individual contributor role, you will act as a force multiplier—mentoring a high-performing team of engineers, setting rigorous technical standards, and fostering a culture of engineering excellence, innovation, and continuous improvement.

What You'll Be Doing:

• Technical Leadership & Mentorship:
• Serve as the technical anchor for a high-performing team of data and infrastructure engineers building out Motional’s Data Stack.
• Influence the technical roadmap, architectural priorities, and project scoping in alignment with broader engineering objectives.
• Provide deep technical guidance, peer mentorship, and establish rigorous engineering standards and best practices for the team.
  
  
• Architecture, Strategy & Execution:
• Define and execute the technical vision and architecture for storing metrics and generating ML datasets for large computer vision and behavioral models.
• Identify, evaluate, and prototype cutting-edge technologies and methodologies for speeding up data loaders for training, ingestion of metrics, and querying of large datasets for everything from dashboards to training.
• Act as a hands-on contributor for the most complex, high-impact architectural challenges within the data engine space.
  
  
• Cross-functional Collaboration:
• Collaborate closely with ML research, ML Training platform, and data engineering teams to understand their requirements, co-design scalable architectures, and integrate solutions seamlessly.
• Drive technical consensus and communicate complex architectural concepts and strategies to both technical and non-technical stakeholders.
  
  

What We're Looking For:

• Experience:
• BS or MS in Computer Science or related field
• 6+ years of professional experience in data platform engineering
• 3+ years of experience in a technical lead, staff engineer, or senior architecture role, with a proven track record of driving cross-team technical initiatives and mentoring senior engineers.
• Extensive experience with managing large (petabyte plus) scale data platforms such as data warehouses, object storage, and ML training data stores.
• Extensive experience with workflow orchestration frameworks such as Airflow or Step Functions.
  
  
• Technical Skills:
• Core Programming: Strong programming skills in Python. C++ experience is a plus.
• Agentic AI & LLMOps: Proven experience designing, building, and deploying agentic workflows and multi-agent systems using frameworks like LangChain, LlamaIndex, DSPy, or custom LLM orchestration tools for reasoning and automated data processing.
• Storage & Vector Ecosystems: Knowledge of modern data storage formats (Parquet, Iceberg) and vector databases (LanceDB, Milvus, Qdrant) and retrieval architectures (RAG) to manage massive multimodal datasets (video, sensor data, text).
• Cloud & Infrastructure: Strong knowledge of cloud infrastructure (AWS, GCP) solutions, distributed compute, and scalable model serving.
• Domain Experience: Prior experience building data warehouses, lakehouse architectures, or active-learning data loops at an advanced machine learning, robotics, or autonomous vehicle company.
  
  

Bonus Points (not required):

• Prior experience in autonomous vehicles (AV) is a plus.
• Prior experience with Bazel based build systems.
  
  

We encourage a hybrid schedule with in-office time at one of our locations in Boston, Pittsburgh, or Las Vegas to support collaboration, or this role can be fully remote.