{"id":3551458,"url":"https://alion.io/job/novaflow-founding-machine-learning-engineer","title":"Founding Machine Learning Engineer","company":{"id":3779507,"name":"Novaflow","domain":"novaflow.ai","url":"https://alion.io/company/novaflow-2","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Work at a Startup","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"junior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":150000,"max":250000,"currency":"USD","period":"year","gross":null,"usd_annual":250000},"salary_estimate":null,"experience_years_min":1,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"AWS","optional":false},{"name":"Fine-tuning","optional":false},{"name":"GCP","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"RAG","optional":false},{"name":"Anthropic","optional":true},{"name":"CI/CD","optional":true},{"name":"Docker","optional":true},{"name":"Kubernetes","optional":true},{"name":"OpenAI","optional":true},{"name":"Python","optional":true},{"name":"PyTorch","optional":true},{"name":"TensorFlow","optional":true},{"name":"Terraform","optional":true}],"status":"live","first_seen_at":"2026-10-30T22:53:31Z","employer_posted_date":"2026-10-30","last_verified_at":"2026-11-07T06:20:24Z","board_verified":true,"closed_at":null,"days_open":7,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":7},"description":"About Novaflow\nNovaflow is the AI data analyst for biology labs. Analytics is the bottleneck for scientific discovery. Biologists have to outsource analysis to expensive bioinformaticians or core services and wait weeks or months for results. We're solving this by putting analysis directly back into the hands of researchers, allowing them to go from raw data to publication-ready insights and visualizations in days instead of months. We're well-funded, growing extremely fast, and backed by leading investors including Y Combinator and BioRender.\nAbout the Role\nWe're hiring a Founding Machine Learning Engineer to build the AI systems that power our platform. The core challenge: take a natural language query from a biologist and turn it into a correct, reliable bioinformatics workflow. That means working with LLMs, building evaluation systems to know when outputs are good (and when they're not), and shipping models that real scientists depend on every day.\nThis is a high-agency, high-ownership role. You'll work directly with the founders and have real say in our AI strategy. Biology background is not required. What matters is that you're a strong ML engineer who ships.\nThis role is in-person at our San Francisco office. The founding team works side by side every day to make fast decisions and ship.\nWhat You'll Work On\nBuild and improve the LLM-powered pipelines that turn natural language into bioinformatics workflows\nDesign evaluation pipelines and benchmarks to measure model quality against real scientific expectations\nExperiment with fine-tuning, RAG, prompt engineering, and different model architectures\nDeploy and scale models in production on AWS or GCP\nMake build-vs-buy decisions on AI tooling and infrastructure\nWork across the team to integrate ML capabilities into the product\nRequirements\nBachelor's or Master's in Computer Science, Machine Learning, AI, or a related field (PhD is a plus)\n2+ years building and deploying ML models in production\nStrong Python skills and hands-on experience with PyTorch, TensorFlow, or similar\nReal experience with LLMs: fine-tuning, RAG, prompt engineering, evals\nExperience working with large datasets and building data pipelines\nFamiliar with AWS or GCP for model training and deployment\nDocker and CI/CD experience for ML workflows\nCan spot when an LLM is confidently wrong\nNice to Have\nExperience applying ML to scientific or biological data\nFamiliarity with Anthropic, OpenAI, or other LLM APIs and agent frameworks\nTerraform and Kubernetes experience\nStartup background or experience in research-oriented engineering\nPrevious startup experience (prior experience either working for or founding a startup)\nWhy Join Us?\nCompetitive salary and meaningful equity as a founding team member\n401(k) with company match\nUnlimited PTO + federal holidays\nMonthly health and wellness stipend\nMeals covered when you're in the office (lunch daily, dinner when you're working late)\nTeam offsites and company events\nIf you're curious about being a founder one day, this is your front-row seat. 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