Related skills
azure aws python gcp tensorflowπ Description
- Define multi-quarter roadmaps for core ML systems.
- Architect system-level ML products for data mining and real-time inference.
- Drive cross-functional execution; align roadmaps across teams.
- Establish standards for ML design, testing, deployment.
- Apply broad ML techniques to solve complex problems.
- Mentor engineers; lead architectural reviews.
π― Requirements
- BS in CS, ML, or related field; 8+ years of hands-on ML engineering.
- Ownership of architecture, deployment, and optimization of large-scale ML systems.
- Experience with multimodal foundation models in production.
- Technical leadership: roadmaps, multi-team initiatives, strategy.
- Python and ML frameworks (PyTorch, TensorFlow, or JAX); system design, CI/CD, containerization.
- Broad ML generalist knowledge: training, architectures, evaluation, production deployment at scale.
- Cloud deployment in AWS, GCP, or Azure; latency/throughput optimization.
- Mentor peers; communicate trade-offs to drive consensus.
π Benefits
- Hybrid schedule with in-office time at Boston, Pittsburgh, or Las Vegas; or remote.
- Medical, dental, vision, 401k with match, HSA, life and pet insurance.
- Inclusive, people-first culture with growth and collaboration.
- EOE; participates in E-Verify.
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