Staff Software Engineer - AI Data Engine
New
M
MotionalAutonomous vehicles
Boston, Massachusetts, United States; Las Vegas, Nevada, United States; Pittsburgh, Pennsylvania, United States; Remote U.S.Full-TimeStaff
Salary$172,000 — $229,000 USD
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Job Details
- Experience
- 6+ years of professional experience in data platform engineering; 3+ years of experience in a technical lead, staff engineer, or senior architecture role.
- Required Skills
- AWSPythonGCPAirflowMLOpsLangChainDistributed Systems
Requirements
- 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 track record of driving cross-team initiatives.
- 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.
- Strong programming skills in Python (C++ experience is a plus).
- Proven experience designing and deploying agentic workflows and multi-agent systems using frameworks like LangChain, LlamaIndex, DSPy, or custom LLM orchestration tools.
- Knowledge of modern data storage formats (Parquet, Iceberg) and vector databases (LanceDB, Milvus, Qdrant) and retrieval architectures (RAG).
- Strong knowledge of cloud infrastructure (AWS, GCP), distributed compute, and scalable model serving.
- Prior experience building data warehouses, lakehouse architectures, or active-learning data loops at an advanced machine learning, robotics, or autonomous vehicle company.
Responsibilities
- 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.
- 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.
- Act as a hands-on contributor for the most complex, high-impact architectural challenges within the data engine space.
- Collaborate closely with ML research, ML Training platform, and data engineering teams to understand requirements and co-design scalable architectures.
- Drive technical consensus and communicate complex architectural concepts and strategies to both technical and non-technical stakeholders.
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