๐ง๐ต๐ถ๐ ๐ฟ๐ผ๐น๐ฒ ๐ถ๐ ๐ณ๐ผ๐ฟ ๐ผ๐ป๐ฒ ๐ผ๐ณ ๐๐ต๐ฒ ๐ช๐ฒ๐ฒ๐ธ๐ฑ๐ฎ๐'๐ ๐ฐ๐น๐ถ๐ฒ๐ป๐๐
๐ฆ๐ฎ๐น๐ฎ๐ฟ๐ ๐ฟ๐ฎ๐ป๐ด๐ฒ: ๐ฅ๐ ๐ฏ๐ฑ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ - ๐ฅ๐ ๐ฑ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ (๐ถ๐ฒ ๐๐ก๐ฅ ๐ฏ๐ฑ-๐ฑ๐ฌ ๐๐ฃ๐)
Experience: 6+ yrs
Location: Karnataka, Bengaluru
As a Research Scientist Core AI, you will spearhead cuttingโedge research initiatives in deep learning and reinforcement learning, developing and deploying advanced agent frameworks that can scale from prototype to production. You will collaborate with crossโfunctional teams to design highโperformance, distributed systems that power nextโgeneration AI applications, ensuring rigorous experimentation, reproducibility, and impact at scale. Your work will influence both academic publication trajectories and industry product roadmaps, while fostering a culture of curiosity, collaboration, and continuous learning within a fastโpaced research environment.
Requirements
๐๐ฒ๐ ๐ฅ๐ฒ๐๐ฝ๐ผ๐ป๐๐ถ๐ฏ๐ถ๐น๐ถ๐๐ถ๐ฒ๐
โข Design and implement novel deep learning architectures for largeโscale AI workloads
โข Develop reinforcement learning agents and training pipelines for complex environments
โข Prototype and deploy distributed agent frameworks on cloud and edge platforms
โข Optimize model inference and training performance on heterogeneous hardware
โข Conduct rigorous experimentation, A/B testing, and statistical analysis of results
โข Publish findings in top-tier conferences and journals while complying with openโaccess policies
โข Mentor junior researchers and interns, providing technical guidance and career development
โข Collaborate with product teams to translate research insights into viable system features
โข Maintain and improve ML infrastructure tooling, including data pipelines and CI/CD workflows
โข Stay abreast of emerging AI research and technology trends, sharing knowledge with the broader community
๐ช๐ต๐ฎ๐ ๐ ๐ฎ๐ธ๐ฒ๐ ๐ฌ๐ผ๐ ๐ฎ ๐๐ฟ๐ฒ๐ฎ๐ ๐๐ถ๐
โข Ph.D. or equivalent in Computer Science, Machine Learning, or related field with a strong publication record
โข 6+ years of industry or academic experience in deep learning and reinforcement learning
โข Proven expertise in building and scaling agent frameworks for complex, realโtime applications
โข Proficiency in Python, CUDA, and distributed computing libraries such as PyTorch, TensorFlow, or JAX
โข Demonstrated ability to prototype, benchmark, and deploy largeโscale ML systems in production
โข Strong analytical skills with a track record of translating data insights into actionable strategies
โข Excellent communication and collaboration skills across interdisciplinary teams
โข Experience mentoring junior talent and leading research projects from concept to execution
โข Familiarity with cloud platforms (AWS, GCP, Azure) and container orchestration (Kubernetes, Docker)
โข Passion for continuous learning, openโsource contributions, and advancing the state of AI research