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.