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python tensorflow pytorch machine learning mlopsπ Description
- Architect and train teacher-student models for multimodal data.
- Build RL-based policy learning and reasoning systems.
- Deploy distilled and RL models to production; optimize latency and throughput.
- Research agentic workflows for autonomous reasoning and planning.
- Drive reliability of Omnitag data platform; scalable, debuggable systems.
- Mentor junior engineers and translate research into scalable solutions.
π― Requirements
- BS in CS/ML or equivalent experience.
- 6+ years ML eng with post-training, optimization, deployment.
- Distillation/teacher-student experience; loss design and evaluation.
- Production/research RL: policy optimization, rewards, simulation.
- Python and ML frameworks: PyTorch, TensorFlow, or JAX.
- Cloud deployment (AWS/GCP/Azure) and inference optimization; software basics.
π Benefits
- Hybrid schedule with in-office time at Boston, Pittsburgh, or Las Vegas, or fully remote.
- Medical, dental, vision, 401k with company match, HSA, life, and pet insurance.
- We are an equal opportunity employer; E-Verify compliant.
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