AI – Machine Learning Engineer
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Job Description
AI / Machine Learning Engineer developing and deploying ML and GenAI capabilities into applications remotely. Collaborating with product and data teams in a remote environment in the United States.
Responsibilities:
- Develop and deploy ML and GenAI capabilities into production applications
- Build and improve ML models and LLM-powered features (RAG, agents, or classification/NLP as needed)
- Prepare training and evaluation datasets; implement reproducible experiments
- Integrate models into applications via APIs, batch jobs, or real-time services
- Implement monitoring for drift, latency, cost, and quality; iterate from feedback
- Collaborate with product, data engineering, and security on responsible AI practices
- Document architectures, prompts, evaluation metrics, and runbooks
- Support CI/CD and containerized deployment of ML services
Requirements:
- 4+ years in machine learning engineering or applied ML roles
- Strong Python and ML libraries (scikit-learn, PyTorch or TensorFlow)
- Experience deploying models to cloud (AWS, Azure, or GCP)
- Familiarity with LLMs, embeddings, and vector search for GenAI use cases
- Solid software engineering practices: Git, testing, code review
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