Senior Data Scientist focused on data engineering, responsible for discovering, connecting, transforming, and operationalizing engineering data for downstream AI systems and applications.
Compensation
$90,900.00 - $189,800.00
Responsibilities
Discover engineering data and knowledge sources across distributed systems and repositories
Build data-ingestion and integration pipelines
Connect structured and unstructured engineering data
Implement metadata, cataloging, lineage, and discoverability capabilities
Establish data quality, validation, and observability practices
Requirements
Bachelor’s degree in data engineering, computer science, engineering, or related field
As a senior member of our team, the Engineering Manager leads the engineers who build and deliver our clients' data and AI systems.
Locations (4)
Walnut Creek, California, United States
San Francisco, California, United States
Dallas, Texas, United States
Washington, United States
Compensation
This position is also eligible for bonus compensation.
Responsibilities
Lead one or more engineering teams through client engagements, turning data and AI strategy into working systems
Manage the full delivery lifecycle, from technical design and architecture decisions through implementation, code review, testing, and production hand-off
Principal/Staff Technical Program Manager, Engineering
Lead cross‑functional program management for Simbe’s autonomous shelf‑scanning robot, coordinating hardware, ROS software, AI models, and cloud systems to deliver production‑ready robots in retail stores.
Responsibilities
Define and own program schedules for new Tally generations, fleet‑wide migrations, and large retail rollouts
Coordinate integration checkpoints across hardware, ROS software, CV model deployment, cloud pipelines, and retailer dashboards
Ensure deployment readiness and handoff from engineering to field operations
Map dependencies and maintain a standing cross‑functional review cadence
Identify and document top risks with actionable mitigation plans
Hire, coach, and grow engineers, setting technical standards and building feedback loops, career paths, and mentorship
Partner directly with client engineering and technology leaders as a peer, translating ambiguous business requirements into a clear technical plan
Make and stand behind architecture and technology choices for data platforms and AI/ML systems, including cloud-native data lakes and warehouses, pipeline orchestration, and MLOps tooling
Requirements
Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience
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