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aws kubernetes computer vision machine learning spark📋 Description
- Design, build, and operate the end-to-end ML platform (training, inference, edge).
- Partner with product/ML teams to design and launch ML features (CV, EcoDriving, LLM reports).
- Lead throughput and cost estimation for ML features from exploration to production.
- Collaborate on experiment design and evaluation, including metrics and A/B tests.
- Evolve training/experimentation infra and standardize tracking and testing.
- Design and operate scalable Ray/Spark online and batch inference with observability.
🎯 Requirements
- 10+ years in machine learning engineering or related fields.
- Strong experience with Ray and/or Spark.
- AWS, Kubernetes, and production observability tooling.
- Proven experience building or supporting ML platforms used by multiple teams.
- Solid ML fundamentals: evaluation, experiment design, production iteration.
- CV/LLM in production; edge/on-device ML; model registry (nice to have).
🎁 Benefits
- Flexible, employee-led remote model with optional in-person offices.
- Professional development stipend.
- Comprehensive health and parental leave plans.
- Competitive total rewards with base pay, bonus, and equity.
- Support for remote work aligned to operations.
- Accommodations available during recruiting.
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