𝗧𝗵𝗶𝘀 𝗿𝗼𝗹𝗲 𝗶𝘀 𝗳𝗼𝗿 𝗼𝗻𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗪𝗲𝗲𝗸𝗱𝗮𝘆'𝘀 𝗰𝗹𝗶𝗲𝗻𝘁𝘀

𝗦𝗮𝗹𝗮𝗿𝘆 𝗿𝗮𝗻𝗴𝗲: 𝗥𝘀 𝟯𝟱𝟬𝟬𝟬𝟬𝟬 - 𝗥𝘀 𝟱𝟬𝟬𝟬𝟬𝟬𝟬 (𝗶𝗲 𝗜𝗡𝗥 𝟯𝟱-𝟱𝟬 𝗟𝗣𝗔)

Experience: 6+ yrs

Location: Karnataka, Bengaluru

As a Research Scientist Core AI, you will spearhead cutting‑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 cross‑functional teams to design high‑performance, distributed systems that power next‑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 fast‑paced research environment.

Requirements

𝗞𝗲𝘆 𝗥𝗲𝘀𝗽𝗼𝗻𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝗶𝗲𝘀

• Design and implement novel deep learning architectures for large‑scale AI workloads

• Develop reinforcement learning agents and training pipelines for complex environments

• Prototype and deploy distributed agent frameworks on cloud and edge platforms

• Optimize model inference and training performance on heterogeneous hardware

• Conduct rigorous experimentation, A/B testing, and statistical analysis of results

• Publish findings in top-tier conferences and journals while complying with open‑access policies

• Mentor junior researchers and interns, providing technical guidance and career development

• Collaborate with product teams to translate research insights into viable system features

• Maintain and improve ML infrastructure tooling, including data pipelines and CI/CD workflows

• Stay abreast of emerging AI research and technology trends, sharing knowledge with the broader community

𝗪𝗵𝗮𝘁 𝗠𝗮𝗸𝗲𝘀 𝗬𝗼𝘂 𝗮 𝗚𝗿𝗲𝗮𝘁 𝗙𝗶𝘁

• Ph.D. or equivalent in Computer Science, Machine Learning, or related field with a strong publication record

• 6+ years of industry or academic experience in deep learning and reinforcement learning

• Proven expertise in building and scaling agent frameworks for complex, real‑time applications

• Proficiency in Python, CUDA, and distributed computing libraries such as PyTorch, TensorFlow, or JAX

• Demonstrated ability to prototype, benchmark, and deploy large‑scale ML systems in production

• Strong analytical skills with a track record of translating data insights into actionable strategies

• Excellent communication and collaboration skills across interdisciplinary teams

• Experience mentoring junior talent and leading research projects from concept to execution

• Familiarity with cloud platforms (AWS, GCP, Azure) and container orchestration (Kubernetes, Docker)

• Passion for continuous learning, open‑source contributions, and advancing the state of AI research