Senior Associate AI ML Engineer

About the role

Riveron is seeking a Senior Associate – AI ML Engineer to build and deploy machine learning and Generative AI applications across the full product lifecycle. Day-to-day work includes designing RAG and agentic AI workflows, integrating foundation models, developing production Python services and APIs, containerizing with Docker, and collaborating with cross-functional teams to deliver enterprise-grade solutions. This full-time role is based in Pune, India and is remote.

What you’ll do

• Build and maintain end-to-end AI/ML and Generative AI applications, including data pipelines, model or prompt workflows, APIs, evaluation, deployment, and monitoring.
• Design Retrieval-Augmented Generation (RAG) solutions using document ingestion, chunking, embeddings, vector search, reranking, citations, and access-aware retrieval.
• Develop agentic AI workflows that use tools, structured outputs, state or memory, orchestration, guardrails, human-in-the-loop approvals, and failure recovery.
• Integrate foundation models and AI services from commercial and open-source ecosystems; select models based on quality, latency, cost, privacy, and deployment constraints.
• Implement prompt engineering, few-shot patterns, function/tool calling, structured output validation, and—where justified—fine-tuning or parameter-efficient tuning.
• Create reproducible evaluation pipelines for accuracy, relevance, groundedness, safety, latency, reliability, and cost; maintain regression or “golden” test datasets.
• Develop production services using Python, REST APIs, asynchronous processing, and well-defined interfaces; write clean, modular, documented, and testable code.
• Use Git and GitHub for version control, pull requests, code review, issue tracking, and release management; implement CI/CD workflows with GitHub Actions or equivalent tools.

What you’ll bring

• Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Engineering, or a related field—or equivalent practical experience.
• 3–5 years of professional experience developing software, data, or machine learning solutions, including substantial hands-on experience with Generative AI or LLM-based applications.
• Strong Python programming skills and practical experience with common data and ML libraries such as pandas, NumPy, scikit-learn, PyTorch, TensorFlow, or equivalent.
• 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, working with JSON and schemas, and integrating databases, enterprise systems, or external services.
• Understanding of software-engineering practices: object-oriented or modular design, unit and integration testing, logging, error handling, code review, documentation, and debugging.
• Hands-on experience with Git/GitHub and CI/CD concepts; ability to create or maintain automated build, test, security-scan, and deployment workflows.
• A current, role-relevant AWS AI/ML certification or Microsoft Azure AI certification is mandatory.

Nice to have

• Experience with one or more GenAI/agent frameworks or SDKs, such as OpenAI Agents SDK, LangGraph/LangChain, Semantic Kernel, LlamaIndex, AutoGen, or similar.
• Experience with vector stores or search platforms such as pgvector, Pinecone, Weaviate, Milvus, Elasticsearch/OpenSearch, Azure AI Search, or equivalent.
• Exposure to LLMOps/MLOps tooling for experiment tracking, tracing, evaluation, model registry, prompt management, or monitoring (for example, MLflow or comparable platforms).
• Knowledge of SQL and data modeling; exposure to streaming, queues, workflow orchestration, or distributed processing is a plus.
• Experience applying AI to enterprise use cases such as finance, accounting, operations, customer service, document intelligence, software engineering, analytics, or workflow automation.
• Awareness of responsible AI, bias and risk assessment, data governance, secure development, and regulatory or client-compliance requirements.
• Open-source contributions, technical writing, hackathon projects, or a portfolio demonstrating deployed AI applications.

Skills

Benefits

• Medical, dental, and vision insurance
• 401(k) with company match
• PTO

Education

Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Engineering, or a related field—or equivalent practical experience