Lead AI Dataloop and Release Engineer
Merlin is a Boston-based aerospace and defense technology company developing AI-powered, aircraft-agnostic autonomy software for fixed-wing aircraft.
About Merlin
Merlin’s Merlin Pilot combines hardware and software intended to perform takeoff-to-touchdown flight functions for military and civil aircraft, supporting reduced-crew and autonomous operations. The operating business began as Apollo Flight Research in 2018, became Merlin Labs in 2020, and is now operated under public parent Merlin, Inc.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will define and execute data strategy for model training, simulation, and production deployment. You will own data pipelines, flywheels, training-cluster integration, and simulator data integration. You will establish data quality and traceability standards, lead data and infrastructure engineers, and track pipeline, simulation, and model-readiness metrics.
Requirements
- Degree in Computer Science, Artificial Intelligence, Data Science, Computer Engineering, Applied Math, or a related subject
- 10+ years of engineering experience
- At least 4 years of technical leadership in data infrastructure, MLOps, or AI platform engineering
- Experience building production data pipelines for AI and ML training
- Experience with dataset management, labeling workflows, and data versioning
- Experience with GPU or TPU clusters, job orchestration, and experiment tracking
- Understanding of simulation pipelines and simulator fidelity
- Experience in safety-critical domains
- Experience building reliable platforms and tooling for engineering teams
Responsibilities
- Define and execute data strategy for AI training, simulation, and production deployment
- Own data pipelines from collection and labeling through curation, versioning, and delivery
- Build data flywheels from deployed behavior to future training iterations
- Align data delivery with GPU and TPU training clusters
- Design data pipelines for data-driven, physics-based, and high-fidelity simulators
- Establish regulatory data quality and traceability standards
- Lead, mentor, and grow data and infrastructure engineers
- Define and track pipeline-health, simulation-fidelity, and model-readiness KPIs
Benefits
- Equity grants
- Catered lunches
- Snacks and beverages
- Health insurance
- Dental insurance
- Life insurance
- Unlimited vacation
- 401k matching