Overview
Senior Associate – AI/ML Engineer role focused on building and deploying machine learning and Generative AI applications across the product lifecycle.
What you'll do
- Build and maintain end-to-end AI/ML and Generative AI applications across data pipelines, prompt/model workflows, APIs, evaluation, deployment, and monitoring.
- Design Retrieval-Augmented Generation (RAG) solutions including ingestion, chunking, embeddings, vector search, reranking, citations, and access-aware retrieval.
- Develop agentic AI workflows with tools, structured outputs, state/memory, orchestration, guardrails, approvals, and failure recovery.
- Integrate foundation models and AI services, selecting options based on quality, latency, cost, privacy, and deployment constraints.
- Implement prompt engineering and structured output validation, including few-shot patterns and tool/function calling.
- Create reproducible evaluation pipelines and maintain regression/golden test datasets.
What you'll need
- 3–5 years of professional experience developing software, data, or ML solutions, including hands-on Generative AI/LLM applications.
- Strong Python skills and experience with pandas, NumPy, scikit-learn, PyTorch, and/or TensorFlow.
- Working knowledge of LLM application patterns such as prompting, embeddings, RAG, vector databases, tool/function calling, structured outputs, and agent workflows.
- Experience building and consuming REST APIs with JSON and schemas.
- Knowledge of software-engineering practices including modular design, testing, logging, error handling, and debugging.
- Hands-on Git/GitHub experience and CI/CD concepts.
- A current role-relevant AWS AI/ML certification or Microsoft Azure AI certification is mandatory.
Details
Read the full description and apply on the company’s own careers page.