{"id":4194754,"url":"https://alion.io/job/google-deepmind-gemini-vision-research-scientist","title":"Gemini Vision Research Scientist","company":{"id":4,"name":"Google DeepMind","domain":"deepmind.google","url":"https://alion.io/company/deepmind","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Career site","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Mountain View, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AutoGen","optional":false},{"name":"CrewAI","optional":false},{"name":"Fine-tuning","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"Multimodal AI","optional":false},{"name":"Post-training","optional":false},{"name":"Pre-training","optional":false},{"name":"LangChain","optional":true}],"status":"live","first_seen_at":"2026-11-12T14:38:24Z","employer_posted_date":"2026-11-12","last_verified_at":"2026-11-12T20:18:03Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"About the job\nAs an organization, Google maintains a portfolio of research projects driven by fundamental research, new product innovation, product contribution and infrastructure goals, while providing individuals and teams the freedom to emphasize specific types of work. As a Research Scientist, you'll setup large-scale tests and deploy promising ideas quickly and broadly, managing deadlines and deliverables while applying the latest theories to develop new and improved products, processes, or technologies. From creating experiments and prototyping implementations to designing new architectures, our research scientists work on real-world problems that span the breadth of computer science, such as machine (and deep) learning, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more.\nAs a Research Scientist, you'll also actively contribute to the wider research community by sharing and publishing your findings, with ideas inspired by internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world.\nArtificial intelligence will be one of humanity’s most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.\nWe are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.\nIndividual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits\nLearn more about benefits at Google.\nResponsibilities\nDesign, implement, and scale state-of-the-art LLM's core image/video understanding capabilities.\nDrive end-to-end experimental workflows across pre-training and post-training.\nBuild robust, scalable infra and data pipelines to support high-quality multimodal training and eval benchmarks.\nPartner closely with Research Scientists and SWEs to transition cutting-edge research prototypes into production-ready foundation models, striking the right balance between rapid prototyping, maintainability, and generality.\nAnalyze complex experiment metrics and failure modes across multimodal benchmarks to identify opportunities for model quality hillclimbing.\nQualifications\nMinimum qualifications:\n3 years of experience in software engineering or related technical field.\n2 years of work experience in an applied research setting.\n\nExperience in Artificial Intelligence or Machine Learning.\nExperience developing autonomous agents, multi-agent workflows, or agentic frameworks (e.g., AutoGen, CrewAI, LangGraph, tool-use/function-calling, or multi-agent RL); 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