{"id":3288552,"url":"https://alion.io/job/sandboxaq-machine-learning-scientist-generative-molecular-design-material-discovery","title":"Machine Learning Scientist, Generative Molecular Design (Material Discovery)","company":{"id":7529,"name":"SandboxAQ","domain":"sandboxaq.com","url":"https://alion.io/company/sandboxaq","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":134400,"max":252000,"currency":"USD","period":"year","gross":null,"usd_annual":252000},"salary_estimate":null,"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Braintrust","optional":false},{"name":"GCP","optional":false},{"name":"JAX","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"PyTorch","optional":false},{"name":"TensorFlow","optional":false},{"name":"Fine-tuning","optional":true},{"name":"LoRA","optional":true},{"name":"PEFT","optional":true},{"name":"Reinforcement Learning","optional":true}],"status":"live","first_seen_at":"2026-10-26T19:01:04Z","employer_posted_date":"2026-10-26","last_verified_at":"2026-11-01T09:35:49Z","board_verified":true,"closed_at":null,"days_open":5,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":5},"description":"About SandboxAQ\nSandboxAQ is a high-growth company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) power advances in life sciences, financial services, navigation, cybersecurity, and other sectors.\nWe are a global team that is tech-focused and includes experts in AI, chemistry, cybersecurity, physics, mathematics, medicine, engineering, and other specialties. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors and supported by a braintrust of industry leaders.\nAt SandboxAQ, we’ve cultivated an environment that encourages creativity, collaboration, and impact. By investing deeply in our people, we’re building a thriving, global workforce poised to tackle the world's epic challenges. Join us to advance your career in pursuit of an inspiring mission, in a community of like-minded people who value entrepreneurialism, ownership, and transformative impact.\nThe Opportunity\nIntroduction to the team: The AI Simulation (AI Sim) division at SandboxAQ applies physics and AI simulation to problems in drug discovery and the material sciences. You will work within a highly skilled, multidisciplinary team of computational chemists, physicists, AI experts, and software engineers, on a generative platform that is used across both application areas.\nIntroduction to the role: We are looking for a Machine Learning Scientist to help build the generative engine at the centre of SandboxAQ's material discovery work. The platform finds compounds that match a desired property profile by navigating chemical space while balancing multiple competing objectives. You will: (1) implement, extend, and optimize frontier generative architectures for material discovery; (2) own the interface between the generative engine and the property predictors that supply its reward signal; (3) identify, ingest, and quality-control the data these models are trained and evaluated on; and (4) turn the models you build into production capability that discovery scientists across the company can run.\nSee how SandboxAQ is helping build America's semiconductor supply chain from the materials up\nKey Responsibilities\nArchitect and evolve our flagship generative platform, serving as a core contributor to the engine that will redefine how the industry discovers new materials.\n\nImplement and optimize state-of-the-art generative models - including diffusion, flow-matching, and GFlowNets, or LLM- and agent-based methods - to navigate high-dimensional chemical space and solve the multi-objective optimization problems that material discovery presents.\n\nOwn the reward interface. Integrate learned surrogates, and simulation-derived oracles as the objective signal driving generation, and design reward formulations that hold up when several objectives are in genuine tension e.g. performance against environmental and safety constraints.\n\nDevelop and deploy computational methods and workflows to generate and evaluate hypotheses, guiding design decisions and influencing project direction.\n\nIdentify relevant data sources and take responsibility for data ingestion, QC, and validation.\n\nCollaborate daily with a core group of ML researchers to implement frontier generative architectures, while working closely with the broader R&D, discovery, engineering, and product teams.\n\nEssential Skills & Experience\nHands-on expertise building and shipping modern generative or applied ML for material discovery with at least 4+ years of experience delivering these solutions in industry or an equivalent research setting.\n\nDemonstrated ability to write clean, maintainable, and robust production-grade code designed for industry-scale applications.\n\nProven ability to build scalable ML, e.g. using PyTorch, TensorFlow, or JAX.\n\nFamiliarity with cloud-based platforms (e.g. Google Cloud Platform, AWS) for compute and data processing and storage.\n\nPhD or MSc in Computational Chemistry, Physics, Computer Science, or equivalent.\n\nExcellent communication skills and a record of fostering successful internal collaboration in a fast-paced environment.\n\nExperience developing ML code in a collaborative environment using modern software engineering best practices.\n\nHighly Desired Skills & Experience\nWe are growing this team across three areas of generative expertise, listed in the order we most need them. You do not need all three - deep, hands-on strength in any one of them is what we are looking for.\nActive learning and bayesian optimization. Driving a design-make-test loop with an expensive oracle such as a physics simulation (DFT, molecular dynamics) or an experimental lab-in-the-loop assay.\n\nGuided generative modeling for material discovery; generation constrained to makeable chemical space; inference-time steering (guided diffusion, sequential monte-carlo and related approaches) or fine-tuning (LoRA, reinforcement learning) for adapting general models to a particular domain of interest;.\n\nAgentic and LLM approaches to material discovery.\n\nWhy Join Us?\nWe offer competitive compensation, a comprehensive benefits package, and opportunities for professional growth.\nCompensation: Competitive base salary commensurate with experience, plus equity and performance-based incentives.\n\nBenefits: Comprehensive health, dental, and vision insurance; 401(k) with company match; generous parental leave.\n\nWork-Life Balance: Flexible hybrid work arrangements, generous PTO, and a culture that respects focus time and recovery.\n\nCareer Development: Direct exposure to CHIPS Act-funded programs, senior scientific and executive leadership, mentorship, and dedicated learning budgets to support continued growth.\n\nSandboxAQ Welcomes All\nWe are committed to fostering a culture of belonging and respect, where diverse perspectives are actively sought and valued. Our multidisciplinary environment provides ample opportunity for continuous growth - working alongside humble, empowered, and ambitious colleagues ready to tackle epic challenges.\nEqual Employment Opportunity: All qualified applicants will receive consideration regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status.\nAccommodations: We provide reasonable accommodations for individuals with disabilities in job application procedures for open roles. If you need such an accommodation, please let a member of our Recruiting team know.\nRead:Guidance for candidates on using AI Tools in interviews","description_format":"text","description_chars":6599,"description_truncated":false,"requirements":{"experience_years_min":4,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"master","optional":false},"security_clearance":false,"languages":[]},"benefits":["Equity","Hybrid work","Parental leave","Vision insurance"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Quantum Science & Computing","Information Security","AI for Science"],"lifecycle":[{"event":"open","at":"2026-10-26T19:20:20Z"}],"visa":[],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":5,"expected_fill_days":77,"reasons":["conf:0","velocity","win:early"],"computed_at":"2026-11-01T06:10:25Z"},"pay":{"stated_usd_annual":252000,"is_top_pay":true},"html_url":"https://alion.io/job/sandboxaq-machine-learning-scientist-generative-molecular-design-material-discovery","json_url":"https://alion.io/job/sandboxaq-machine-learning-scientist-generative-molecular-design-material-discovery.json","meta":{"generated_at":"2026-11-01T12:19:52Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":18974,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-11-02T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":7529},"rest":"https://alion.io/mcp/rest/get_company?id=7529"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fsandboxaq-machine-learning-scientist-generative-molecular-design-material-discovery"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fsandboxaq-machine-learning-scientist-generative-molecular-design-material-discovery"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fsandboxaq-machine-learning-scientist-generative-molecular-design-material-discovery"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/sandboxaq-machine-learning-scientist-generative-molecular-design-material-discovery\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fsandboxaq-machine-learning-scientist-generative-molecular-design-material-discovery"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":3288552}},{"tool":"search_jobs","arguments":{"company":"sandboxaq.com","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":3288552},"note":"people open to offers who fit this vacancy"}],"note":"The same data through MCP tools: https://alion.io/mcp/open needs no sign-in (compact searches, postings, people); https://alion.io/mcp with an Alion account has everything. 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