AI Research Engineer II

𝗔𝗯𝗼𝘂𝘁 𝘁𝗵𝗲 𝗷𝗼𝗯

This role is for one of our client companies — a VC-backed Technology, Information and Internet startup that has raised $2.25M USD in funding.

𝗦𝗮𝗹𝗮𝗿𝘆: Up to 35LPA

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 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵𝗲𝗿 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿 - 𝗜𝗜 (2+ 𝗬𝗲𝗮𝗿𝘀 𝗼𝗳 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲)

We’re looking for an AI Research Engineer with 2-4 years of experience to bridge the gap between applied research and production-grade AI systems. In this role, you will design, build, and optimize Python-based LLM and RAG solutions to transform complex health data.

🧩 𝗪𝗵𝗮𝘁 𝗬𝗼𝘂'𝗹𝗹 𝗗𝗼

• Review relevant research literature and identify techniques applicable to real-world AI problems.
• Formulate hypotheses, design experiments, and validate research findings against proprietary datasets.
• Build, deploy, and maintain production-quality AI systems using Python.
• Design and optimize embedding-based retrieval pipelines, including vector search, chunking, indexing, and ranking.
• Develop robust RAG and LLM-based systems with effective context construction and structured outputs.
• Create evaluation harnesses, benchmarks, and testing workflows to measure system quality and reliability.
• Define success metrics and baselines before experimentation, then conduct error analysis and iterate on results.
• Improve AI system accuracy, reliability, latency, and scalability through systematic experimentation.✅ 𝗬𝗼𝘂'𝗿𝗲 𝗮 𝗚𝗿𝗲𝗮𝘁 𝗙𝗶𝘁 𝗜𝗳 𝗬𝗼𝘂
• 2-4 years of experience in applied AI research, ML engineering, or production AI development.
• Strong Python programming skills and solid SQL fundamentals.
• Hands-on experience building and deploying production-grade AI/ML systems.
• Strong understanding of embeddings, semantic search, vector databases, and information retrieval.Experience building and optimizing RAG pipelines, including chunking, indexing, retrieval, and context construction.
• Practical experience developing LLM-powered applications with structured outputs and prompt engineering.
• Experience designing evaluation frameworks, benchmarks, and systematic testing pipelines for AI systems.✨ 𝗪𝗵𝘆 𝗝𝗼𝗶𝗻 𝗨𝘀?
• Own your research from concept to production with complete autonomy.
• Build breakthrough AI systems that directly shape our early-stage product.
• Accelerate your career alongside top-tier engineers in a fast-paced environment.
• Work closely with founders to solve complex, high-impact technical challenges.