AI Engineer (Upto 70LPA)

𝗔𝗯𝗼𝘂𝘁 𝘁𝗵𝗲 𝗷𝗼𝗯

This role is for one of our client companies — a VC-backed startup that has raised $11M USD in funding.

𝗦𝗮𝗹𝗮𝗿𝘆: Up to 70LPA

Apply once and, if selected, get access to up to 20 remote and onsite interview opportunities.

🚀 𝗪𝗵𝗮𝘁 𝗪𝗲'𝗿𝗲 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴

CodeRound AI matches the top 5% tech talent with the fastest-growing, VC-funded AI startups across Silicon Valley and India.

Top-tier product startups across the US, UK, EU, UAE, and India have hired top engineers through CodeRound.

🚀 𝗔𝗜 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿 (4+ 𝗬𝗲𝗮𝗿𝘀 𝗼𝗳 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲)

We are seeking a Senior AI Engineer to own the applied LLM and retrieval infrastructure for a high-growth healthcare technology startup. In this role, you will design and scale production-grade AI systems, leveraging open-source models to automate complex clinical workflows.

🧩 𝗪𝗵𝗮𝘁 𝗬𝗼𝘂'𝗹𝗹 𝗗𝗼

• Self-Hosted LLM Infrastructure: Deploy, fine-tune, and operate open-source LLMs as the primary inference stack, optimizing GPU utilization, throughput, latency, batching, and inference costs.
• Model Fine-Tuning: Own end-to-end fine-tuning workflows using SFT, LoRA, QLoRA, and DPO to adapt models to clinical notes, claims, and payer-specific data.
• Knowledge Graph Engineering: Design and maintain knowledge graphs representing medical coding standards, healthcare policies, payer rules, and relationships across coding systems.
• Retrieval Systems: Build and optimize embedding-based retrieval pipelines using chunking, embedding models, hybrid search, vector databases, and reranking.
• Grounded AI Systems: Combine graph traversal and dense retrieval to ensure coding recommendations, claim edits, and appeal responses are backed by reliable and auditable evidence.
• Evaluation Infrastructure: Build continuous evaluation pipelines and offline benchmarks using human-validated datasets to assess model accuracy, retrieval quality, and system reliability.
• Production Monitoring: Monitor hallucinations, model drift, regressions, and output quality through shadow deployments, cohort-level accuracy tracking, and production observability.
• LLM Application Development: Design prompts, context pipelines, structured outputs, and function-calling workflows for medical coding, denial classification, claim edits, and appeal generation.✅ 𝗬𝗼𝘂'𝗿𝗲 𝗮 𝗚𝗿𝗲𝗮𝘁 𝗙𝗶𝘁 𝗜𝗳 𝗬𝗼𝘂
• 4+ years of experience in AI/ML Engineering, Machine Learning, or Applied AI, including at least 6 months of hands-on production LLM experience.
• Strong proficiency in Python, PyTorch, and Hugging Face Transformers.
• Hands-on experience deploying, serving, and operating self-hosted open-source LLMs using vLLM, SGLang, TensorRT-LLM, or equivalent inference frameworks.
• Strong understanding of LLM inference optimization, including GPU utilization, batching, KV-cache management, throughput, latency, and serving costs.
• Experience designing embedding-based retrieval systems and/or knowledge graphs for grounded LLM applications.
• Strong understanding of RAG architectures, including document chunking, embedding generation, hybrid search, retrieval optimization, and reranking.✨ 𝗪𝗵𝘆 𝗝𝗼𝗶𝗻 𝗨𝘀?
• Build and ship production AI systems with complete technical ownership.
• Create massive real-world impact at a well-funded Series A startup.
• Accelerate your career growth by solving complex, unsolved engineering challenges.
• Work alongside an elite team of ambitious and highly driven builders.