FreeHire

GIST Impact

SDE 2 - AI/ML

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Role Description:
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We are looking for a highly motivated AI Engineer with 2\u20133 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.
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Key Responsibilities:<\/span><\/b>
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  • Design, build, and deploy end\-to\-end AI/ML systems with a focus on real\-world applications
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  • Develop and optimise LLM\-powered applications, including chat systems, copilots, and agent\-based workflows
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  • Build scalable APIs and backend systems to serve AI models in production
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  • Work on retrieval\-augmented generation (RAG) pipelines and vector search systems
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  • Collaborate with cross\-functional teams (product, design, data) to deliver features rapidly
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  • Ensure production readiness through proper testing, monitoring, and optimisation
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  • Mentor junior engineers and contribute to team knowledge sharing
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  • Continuously explore and integrate emerging AI tools, frameworks, and best practices
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    Requirements<\/h3>
    • Experience<\/span>
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      • 2\u20133 years of experience in AI/ML + Software Engineering roles
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      • Programming & Engineering
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        • Strong proficiency in Python
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        • Understanding of system design
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        • Experience building REST APIs / microservices
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        • MLOps & Infrastructure Experience with:
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          • Docker (containerization)
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          • Kubernetes (deployment & scaling)
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          • CI/CD pipelines for ML systems
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          • Familiarity with cloud platforms (AWS / GCP / Azure)
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          • AI / ML & LLM Stack Hands\-on experience with:
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            • LLMs & GenAI Prompt engineering, fine\-tuning basics
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            • Frameworks & Libraries like LangChain / LlamaIndex
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            • Hugging Face, PyTorch ecosystem
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            • Retrieval & Search FAISS or other Vector Databases (Pinecone, Weaviate, Chroma, etc.)
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            • Agentic AI Systems, multi\-agent workflows, MCP or similar
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            • Preferred Experience
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              • Experience with document parsing & processing pipelines (e.g., PDFs, tables, OCR, structured extraction)
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              • Exposure to knowledge graphs or hybrid retrieval systems
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              • Familiarity with UI frameworks (StreamLit)
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