SDE 2 - AI/ML
Role Description:
We are looking for a highly motivated AI Engineer with 2–3 years of hands-on experience in building and deploying AI-powered systems. This is a builder-first role, focused on delivering real-world AI applications in fast-paced environments. The ideal candidate is someone who thrives in startup-like settings, takes ownership, moves fast, and enjoys solving practical problems.
We are looking for a highly motivated AI Engineer with 2–3 years of hands-on experience in building and deploying AI-powered systems. This is a builder-first role, focused on delivering real-world AI applications in fast-paced environments. The ideal candidate is someone who thrives in startup-like settings, takes ownership, moves fast, and enjoys solving practical problems.
Key Responsibilities:
- Design, build, and deploy end-to-end AI/ML systems with a focus on real-world applications
- Develop and optimise LLM-powered applications, including chat systems, copilots, and agent-based workflows
- Build scalable APIs and backend systems to serve AI models in production
- Work on retrieval-augmented generation (RAG) pipelines and vector search systems
- Collaborate with cross-functional teams (product, design, data) to deliver features rapidly
- Ensure production readiness through proper testing, monitoring, and optimisation
- Mentor junior engineers and contribute to team knowledge sharing
- Continuously explore and integrate emerging AI tools, frameworks, and best practices
Requirements
- Experience
- 2–3 years of experience in AI/ML + Software Engineering roles
- Programming & Engineering
- Strong proficiency in Python
- Understanding of system design
- Experience building REST APIs / microservices
- MLOps & Infrastructure Experience with:
- Docker (containerization)
- Kubernetes (deployment & scaling)
- CI/CD pipelines for ML systems
- Familiarity with cloud platforms (AWS / GCP / Azure)
- AI / ML & LLM Stack Hands-on experience with:
- LLMs & GenAI Prompt engineering, fine-tuning basics
- Frameworks & Libraries like LangChain / LlamaIndex
- Hugging Face, PyTorch ecosystem
- Retrieval & Search FAISS or other Vector Databases (Pinecone, Weaviate, Chroma, etc.)
- Agentic AI Systems, multi-agent workflows, MCP or similar
- Preferred Experience
- Experience with document parsing & processing pipelines (e.g., PDFs, tables, OCR, structured extraction)
- Exposure to knowledge graphs or hybrid retrieval systems
- Familiarity with UI frameworks (StreamLit)