AI/ML Engineer

Location: Hybrid in Pune or Bangalore, India

Company

hirify.global partners with global multinationals and high-growth private entities to solve complex finance challenges.

What you will do

• Build and maintain end-to-end AI/ML and Generative AI applications, including data pipelines, model and prompt workflows, APIs, deployment, evaluation, and monitoring.
• Design Retrieval-Augmented Generation solutions with document ingestion, chunking, embeddings, vector search, reranking, citations, and access-aware retrieval.
• Develop agentic AI workflows with tools, structured outputs, memory, orchestration, guardrails, human approvals, and failure recovery.
• Integrate commercial and open-source foundation models based on quality, latency, cost, privacy, and deployment constraints.
• Develop production services with Python, REST APIs, asynchronous processing, testing, documentation, Git, CI/CD, Docker, and cloud services.
• Apply secure AI practices and collaborate with product, data science, software engineering, cloud, platform, and business stakeholders.

Requirements

• 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 Generative AI or LLM application experience.
• Strong Python skills and practical experience with data and ML libraries such as pandas, NumPy, scikit-learn, PyTorch, or TensorFlow.
• Experience with prompting, embeddings, RAG, vector databases, tool or function calling, structured outputs, agent workflows, REST APIs, JSON, schemas, and integrations.
• Experience with Git/GitHub, testing, code review, CI/CD, at least one cloud platform, and Docker; Kubernetes familiarity is beneficial.
• A current, role-relevant AWS AI/ML certification or Microsoft Azure AI certification is mandatory.

Nice to have

• Experience with GenAI or agent frameworks such as OpenAI Agents SDK, LangGraph, LangChain, Semantic Kernel, LlamaIndex, or AutoGen.
• Experience with vector stores or search platforms such as pgvector, Pinecone, Weaviate, Milvus, Elasticsearch, OpenSearch, or Azure AI Search.
• Exposure to LLMOps/MLOps, SQL, data modeling, streaming, queues, workflow orchestration, or distributed processing.
• Experience applying AI to finance, accounting, operations, customer service, document intelligence, analytics, or workflow automation.
• Open-source contributions, technical writing, hackathon projects, or a portfolio of deployed AI applications.

Culture & Benefits

• Collaborative, entrepreneurial culture guided by Drive, Excellence, Leadership, Teamwork, and Accountability.
• Mentorship, diverse perspectives, and opportunities for professional growth.
• Flexible work environment with progressive benefits and a client-centric approach.
• Full-time benefits include medical, dental, and vision insurance, 401(k) with company match, and paid time off.