Build and productionize ML models across NLP and computer vision. description: Build, train, and productionize ML models across NLP, computer vision, and automation workloads.

Develop reusable training pipelines and evaluation harnesses
Experiment with foundation, open-source, and classical models
Collaborate with product engineers on inference APIs and integrations
Instrument models for telemetry, explainability, and guardrails
Document learnings, benchmarks, and release notes

3 6 years in ML engineering or applied research
Proficiency in Python, PyTorch/TensorFlow, and data processing frameworks
Experience shipping ML workloads into production services
Understanding of prompt engineering, RAG, or CV pipelines
Strong debugging, experimentation, and collaboration skills

Python
PyTorch
TensorFlow
NLP
Computer Vision
RAG
ML Engineering

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AI / ML Engineer

Job Description

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