Applied AI Research Engineer (Bengaluru)

We are an applied AI research organization focused on advancing agent training, reinforcement learning environments, and high-quality data curation for frontier AI systems. Our work spans reasoning datasets, RL environment creation, evaluation frameworks, and scalable infrastructure powering next-generation AI agents. We are looking for exceptional Research Engineers who can operate at the intersection of cutting-edge research and production-grade engineering. About the Role This role is ideal for candidates who thrive in research-heavy environments and enjoy turning novel ideas into scalable systems. You will collaborate closely with researchers, engineers, and external AI teams to design and build robust RL environments, evaluation pipelines, and data curation systems for training advanced agents. The ideal candidate combines strong research fundamentals with hands-on engineering execution. You should be comfortable reading recent ML papers, rapidly prototyping ideas, and productionizing systems at scale. What You’ll Do Research & Applied AI
- Work on reinforcement learning environments, agent training workflows, and evaluation systems.
- Study and implement ideas from recent research papers in RL, reasoning models, and agentic systems.
- Prototype novel approaches for synthetic data generation, curriculum learning, and environment creation.
- Collaborate with research teams to translate experimental ideas into reliable production systems. Engineering & Infrastructure
- Build scalable pipelines for environment generation, validation, deployment, and monitoring.
- Develop automated quality assurance and benchmarking systems.
- Design reproducible workflows and tooling for large-scale research infrastructure.
- Optimize distributed systems and cloud-based ML workflows. Product & Collaboration
- Work closely with technical stakeholders to understand AI training and evaluation requirements.
- Contribute to internal tooling, documentation, and research infrastructure.
- Present technical findings, research insights, and implementation approaches clearly across teams. What We’re Looking For Solid Research Background
- MS/PhD in Computer Science, Machine Learning, Mathematics, Statistics, or related fields preferred.
- Exceptional candidates with strong industry research experience are also encouraged to apply.
- Deep understanding of reinforcement learning, LLMs, reasoning models, agent systems, or related domains.
- Strong ability to read, understand, and implement recent research papers. Technical Skills
- Excellent programming skills in Python.
- Strong experience with PyTorch, JAX, or similar ML frameworks.
- Experience building scalable ML systems or research infrastructure.
- Familiarity with distributed systems, cloud platforms (AWS/GCP), and large-scale experimentation.
- Strong software engineering fundamentals with emphasis on testing, reliability, and maintainability. Ideal Candidate Traits
- Strong ownership mindset and ability to work in fast-paced research environments.
- Excellent communication and collaboration skills.
- Product-oriented thinking with attention to scalability and usability.
- Comfortable working across research and engineering boundaries. Nice to Have
- Hands-on experience with RLHF, RL environments, or agent evaluation systems.
- Contributions to open-source ML projects, datasets, benchmarks, or research tooling.
- Publications at top-tier conferences such as NeurIPS, ICML, ICLR, ACL, or CVPR.
- Experience in applied research, research engineering, or frontier AI startups. Candidate Expectations We are specifically looking for candidates with:
- Exceptional research aptitude and strong problem-solving skills.
- Educational background from premier institutes globally (IITs, IISc, top international universities, or equivalent research-focused institutions).
- Proven exposure to high-impact research, competitive programming, olympiads, publications, or strong open-source/research contributions. Apply on Kit Job: kitjob.in/job/4ll3o4