AI / ML Engineer

We’re looking for a powerhouse AI/ML Engineer to turn cutting-edge research into production-ready reality. You won't just be building prototypes; you’ll be designing, deploying, and scaling GenAI systems that solve real business problems. If you live at the intersection of robust software engineering and advanced machine learning, let’s talk.

Technical Expertise · GenAI & Orchestration: Expert-level development using Lang Chain and Lang Graph ; specialized in multi-step RAG , agentic workflows, and tool-augmented chains. · NLP & Text Processing: Mastery of document parsing, chunking strategies, embeddings, and retrieval optimization. · Core Engineering: Advanced Python (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow) and backend service development using FastAPI . · Vector Infrastructure: Proven experience building and maintaining pipelines with FAISS , AWS Open Search , or similar vector databases. · Cloud Ecosystems (Mandatory): High proficiency in either AWS (SageMaker, Lambda, ECS, Step Functions) or Azure (Azure OpenAI, Functions, App Services). · MLOps & DevOps: Strong grasp of the ML lifecycle—monitoring, versioning (MLflow), and CI/CD pipelines (Jenkins, GitHub Actions). How You’ll Make an Impact Design & Own: Lead end-to-end ML/GenAI workflows, from data ingestion and preprocessing to deployment and inference. Build Production Systems: Architect robust GenAI systems including API design, data pipelines, and scalable monitoring.

Optimize Everything: Continuously evaluate and refine prompts, chains, and agents to improve accuracy while balancing latency and cost efficiency . Collaborate & Integrate: Partner with cross-functional teams to weave AI capabilities into dynamic applications for seamless user experiences. Ensure Excellence: Write high-quality, testable code and conduct rigorous unit/integration testing to ensure system reliability.

Diagnose & Scale: Resolve complex performance and reliability issues across diverse environments. What You Bring Experience: 4+ years of professional experience as an AI, ML, or Software Engineer, specifically building production-grade applications. Education: Bachelor’s degree in Computer Science, Information Technology, or Software Engineering.

Engineering Rigor: A strong software background with experience in version control (Git) and Agile development. Problem Solving: A sharp analytical mind with the communication skills to align technical solutions with business goals.