Research Scientist Core AI

Weekday

Bengaluru, IndiaVerรถffentlicht vor vor 10 Tagen YC W21

รœber die Rolle

๐—ง๐—ต๐—ถ๐˜€ ๐—ฟ๐—ผ๐—น๐—ฒ ๐—ถ๐˜€ ๐—ณ๐—ผ๐—ฟ ๐—ผ๐—ป๐—ฒ ๐—ผ๐—ณ ๐˜๐—ต๐—ฒ ๐—ช๐—ฒ๐—ฒ๐—ธ๐—ฑ๐—ฎ๐˜†'๐˜€ ๐—ฐ๐—น๐—ถ๐—ฒ๐—ป๐˜๐˜€ ๐—ฆ๐—ฎ๐—น๐—ฎ๐—ฟ๐˜† ๐—ฟ๐—ฎ๐—ป๐—ด๐—ฒ: ๐—ฅ๐˜€ ๐Ÿฏ๐Ÿฑ๐Ÿฌ๐Ÿฌ๐Ÿฌ๐Ÿฌ๐Ÿฌ - ๐—ฅ๐˜€ ๐Ÿฑ๐Ÿฌ๐Ÿฌ๐Ÿฌ๐Ÿฌ๐Ÿฌ๐Ÿฌ (๐—ถ๐—ฒ ๐—œ๐—ก๐—ฅ ๐Ÿฏ๐Ÿฑ-๐Ÿฑ๐Ÿฌ ๐—Ÿ๐—ฃ๐—”) Experience: 6+ yrs Location: Karnataka, Bengaluru

As a Research Scientist Core AI, you will spearhead cuttingโ€‘edge 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 crossโ€‘functional teams to design highโ€‘performance, distributed systems that power nextโ€‘generation 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 fastโ€‘paced research environment. Requirements ๐—ž๐—ฒ๐˜† ๐—ฅ๐—ฒ๐˜€๐—ฝ๐—ผ๐—ป๐˜€๐—ถ๐—ฏ๐—ถ๐—น๐—ถ๐˜๐—ถ๐—ฒ๐˜€ โ€ข Design and implement novel deep learning architectures for largeโ€‘scale AI workloads โ€ข Develop reinforcement learning agents and training pipelines for complex environments โ€ข Prototype and deploy distributed agent frameworks on cloud and edge platforms โ€ข Optimize model inference and training performance on heterogeneous hardware โ€ข Conduct rigorous experimentation, A/B testing, and statistical analysis of results โ€ข Publish findings in top-tier conferences and journals while complying with openโ€‘access policies โ€ข Mentor junior researchers and interns, providing technical guidance and career development โ€ข Collaborate with product teams to translate research insights into viable system features โ€ข Maintain and improve ML infrastructure tooling, including data pipelines and CI/CD workflows โ€ข Stay abreast of emerging AI research and technology trends, sharing knowledge with the broader community

๐—ช๐—ต๐—ฎ๐˜ ๐— ๐—ฎ๐—ธ๐—ฒ๐˜€ ๐—ฌ๐—ผ๐˜‚ ๐—ฎ ๐—š๐—ฟ๐—ฒ๐—ฎ๐˜ ๐—™๐—ถ๐˜ โ€ข Ph.D. or equivalent in Computer Science, Machine Learning, or related field with a strong publication record โ€ข 6+ years of industry or academic experience in deep learning and reinforcement learning โ€ข Proven expertise in building and scaling agent frameworks for complex, realโ€‘time applications โ€ข Proficiency in Python, CUDA, and distributed computing libraries such as PyTorch, TensorFlow, or JAX โ€ข Demonstrated ability to prototype, benchmark, and deploy largeโ€‘scale ML systems in production โ€ข Strong analytical skills with a track record of translating data insights into actionable strategies โ€ข Excellent communication and collaboration skills across interdisciplinary teams โ€ข Experience mentoring junior talent and leading research projects from concept to execution โ€ข Familiarity with cloud platforms (AWS, GCP, Azure) and container orchestration (Kubernetes, Docker) โ€ข Passion for continuous learning, openโ€‘source contributions, and advancing the state of AI research

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