{"id":3533937,"url":"https://alion.io/job/weekday-research-scientist-core-ai","title":"Research Scientist Core AI","company":{"id":7097,"name":"Weekday","domain":"weekday.works","url":"https://alion.io/company/weekday","size_band":"51-200","is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":{"grade":"B","score":81,"open_postings":92,"ghost_share":0,"stale_share":0.978,"repost_share":0,"time_to_fill_p50_days":6,"computed_at":"2026-11-03T05:54:40Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"C++","optional":false},{"name":"CUDA","optional":false},{"name":"cuDNN","optional":false},{"name":"Diffusion Models","optional":false},{"name":"Machine Learning","optional":false},{"name":"ML-Agents","optional":false},{"name":"MuJoCo","optional":false},{"name":"OpenAI","optional":false},{"name":"PyBullet","optional":false},{"name":"Python","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"RLlib","optional":false},{"name":"Stable-Baselines3","optional":false},{"name":"Synthetic Data","optional":false},{"name":"PyTorch","optional":true},{"name":"Ray","optional":true}],"status":"live","first_seen_at":"2026-10-30T16:56:58Z","employer_posted_date":"2026-10-30","last_verified_at":"2026-11-03T05:29:33Z","board_verified":true,"closed_at":null,"days_open":3,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":3},"description":"'\n: - ( - )\nExperience: 7+ yrs\nLocation: Bengaluru, Karnataka, India, Karnataka\nAs a Research Scientist Core AI, you will spearhead cutting-edge research and development in reinforcement learning and generative AI, designing intelligent agents that can navigate and thrive in complex simulation environments. You will collaborate with cross-functional teams to translate theoretical breakthroughs into scalable technology stacks, ensuring that our AI systems maintain state-of-the-art performance and robustness. Your role will involve deep experimentation, rigorous benchmarking, and the publication of findings in top conferences and journals, while also mentoring junior researchers and contributing to open source initiatives. You will be the bridge between academic excellence and industrial impact, driving innovation that shapes the future of autonomous AI.\nRequirements\nDevelop and benchmark advanced reinforcement learning algorithms for real-world applications.\nDesign generative models capable of producing high-fidelity synthetic data for training and testing agents.\nBuild and manage scalable agent frameworks that support multi-agent coordination and learning.\nCreate realistic simulation environments that emulate complex dynamics for policy evaluation.\nConduct end-to-end system integration, ensuring seamless interaction between RL agents and simulation back-ends.\nPublish research papers, patents, and technical reports to disseminate knowledge within the community.\nMentor junior scientists and engineers, fostering a culture of continuous learning and collaboration.\nEvaluate emerging AI technologies and propose strategic adoption into product pipelines.\nCollaborate with data engineering teams to curate large-scale datasets and monitor data quality.\nPresent technical findings to stakeholders, translating complex concepts into clear business insights.\nPh.D. or M.S. in Computer Science, Machine Learning, or related field with a strong emphasis on RL or generative models.\n7+ years of industry experience in AI research or a comparable research environment.\nProven track record of published research in top-tier conferences such as NeurIPS, ICML, ICLR, or CVPR.\nExpertise in popular RL libraries (e.g., OpenAI Gym, RLlib, Stable Baselines) and generative frameworks (e.g., GPT, diffusion models).\nProficiency with simulation tools like Unity ML-Agents, MuJoCo, PyBullet, or custom physics engines.\nStrong programming skills in Python, C++, and familiarity with GPU acceleration (CUDA, cuDNN).\nDemonstrated ability to translate theoretical insights into production-grade code.\nExcellent communication skills, able to explain complex technical concepts to non-technical audiences.\nExperience leading cross-disciplinary teams and managing project timelines under resource constraints.\nPassion for staying ahead of AI trends and driving forward-looking research initiatives.","description_format":"text","description_chars":2894,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Continuous 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