{"id":677953,"url":"https://alion.io/job/albertinvent-staff-ml-ops-engineer","title":"Staff ML Ops Engineer","company":{"id":669012,"name":"Albert Invent","domain":"albertinvent.com","url":"https://alion.io/company/albertinvent","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Rippling","truth_index":{"grade":"D","score":49,"open_postings":19,"ghost_share":0.842,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-29T05:49:05Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":[],"countries":[],"hiring_countries":["US"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":164000,"max_usd":309000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":197},"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"ArgoCD","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Flask","optional":false},{"name":"GCP","optional":false},{"name":"Helm","optional":false},{"name":"Kubernetes","optional":false},{"name":"Machine Learning","optional":false},{"name":"Pulumi","optional":false},{"name":"Python","optional":false},{"name":"Rest API","optional":false},{"name":"Terraform","optional":false},{"name":"Apache Kafka","optional":true},{"name":"Dagster","optional":true},{"name":"Datadog","optional":true},{"name":"Grafana","optional":true},{"name":"Prometheus","optional":true},{"name":"RabbitMQ","optional":true},{"name":"Redis","optional":true}],"status":"live","first_seen_at":"2026-02-04T01:17:44Z","employer_posted_date":"2026-02-04","last_verified_at":"2026-10-29T06:04:57Z","board_verified":true,"closed_at":null,"days_open":267,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":267},"description":"Albert’s mission is to digitalize the world of chemistry. Using data and machine learning, Albert enables R&D organizations to dramatically accelerate the invention of new materials. Our platform helps scientists and engineers build structured data foundations, digitize formulation and testing workflows, and apply AI to innovate faster, smarter, and at scale.\nAbout the role\nAs our Backend & Infrastructure Engineer, you will architect and build the core systems that power everything our AI/ML team delivers-the APIs, infrastructure, and distributed systems that make intelligent capabilities possible at scale. This is a foundational role: you'll shape how AI gets built and shipped here.\nWe are seeking a highly motivated and talented individual with deep expertise in Python backend development, Kubernetes, and distributed systems. You'll be embedded with ML engineers and researchers, building robust systems that turn ambitious AI ideas into production realities-whether that's powering agent-based workflows, scaling inference, or enabling scientific computing pipelines. The infrastructure you build will directly enable researchers at the world's largest chemical and materials companies to leverage AI in ways that weren't possible before-accelerating discovery, enabling inverse design of novel materials, and transforming how science gets done.\nWhat you'll do\nInfrastructure & Kubernetes:\nDesign, deploy, andmaintainKubernetes infrastructure supporting AI/ML workloads \nManage containerized services, autoscaling, networking, and resource optimization \nBackend Development:\nDesign and build high-performance Python APIs and services usingFastAPIor similar frameworks \nArchitect backend systems for scalability, reliability, and low latency \nBuild integrations between AI/ML systems and the broaderAlbertplatform \nDistributed Systems:\nBuild andoperatedistributed systems that handle compute-intensive and high-throughput workloads \nDesign for fault tolerance, graceful degradation, and horizontal scalability \nImplement async workflows, job queues, and task orchestration as needed \nData Infrastructure:\nArchitect andmaintaindata pipelines and storage systems supporting AI/ML workflows \nWork with vector databases, caches, and other data stores as required by ML systems \nEnsure efficient data access patterns for training and inference workloads \nReliability & Operations:\nImplement observability including logging, metrics, tracing, and alerting \nOwn system reliability-troubleshoot issues, conduct post-mortems, and continuously improve \nDesign CI/CD pipelines and promote automation best practices \nImplement infrastructure-as-code practices using Terraform, Helm,ArgoCd,Pulumi, or similar tools \nCollaboration:\nPartner closely with ML engineers to understand requirements and deliver production-ready infrastructure \nTranslate ML prototypes and research code into scalable, maintainable systems \nContribute to technical decisions that shape the team's architecture \nYou will have\nDeepexpertisein Python backend development and distributed systems \nStrong Kubernetes and cloud infrastructure experience \nA builder's mindset-you want to create foundational systems that others build on \nGenuine interest in science and technology; curiosity about how your work enables scientific discovery \nA commitment to building systems that are reliable, maintainable, and scalable \nKey competencies\nA degree in Computer Science or a related field with 7+ years of industry experience (Bachelor's) or 5+ years (Master'sor PhD) in software engineering \nExperience supporting AI/ML teams or deploying ML systems in production \nExperience with GPU workloads and scheduling \nAdvancedproficiencyin Python including async programming and performance optimization \nDeep experience with Kubernetes-cluster management, networking, autoscaling, and troubleshooting \nStrong background in distributed systems and microservices architecture \nExperience with cloud platforms (AWS, GCP, or Azure) and infrastructure-as-code \nProficiencyin REST API development usingFastAPI, Flask, or similar \nExperience with containerization and CI/CD pipelines \nTrack recordof operating production systems at scale \nPreferred/Bonus Points\nFamiliarity with scientific computing or research environments \nBackground in or curiosity about chemistry, materials science, or related fields \nFamiliarity with data engineering tools (Airflow,Dagster, or similar) \nExperience with vector databases or search infrastructure \nExpertisein observability tools (Prometheus, Grafana, Datadog) \nExperience with message queues and event-driven architectures (Kafka, Redis, RabbitMQ) \nContributions to open-source projects \nExperience mentoring engineers \nWhy Albert?\nWe have a huge impact. Albert is a growing team with a big reach. Our Platform facilitates the invention of materials for tens of thousands of companies and hundreds of thousands of applications - from coatings used on rockets to adhesives used in electric vehicles to 3D printed medical devices. We love distributed teams. Albert’s home-base is in the California Bay Area, but we have multiple offices and employees sprinkled around the globe. In fact, over 50% of our employees work outside of California! An international remote culture is in our DNA. We care about you. Albert works hard to create a positive environment for our employees, and we think your life outside of work is important too. We work hard and we play hard. We value diversity. Growing and maintaining our inclusive and diverse team matters to us. We are committed to being a company where our employees feel comfortable bringing their authentic selves to work and have the ability to be successful -- every day. We’re always looking for humble, sharp, and creative folks to join the Albert team. If you think you might be a fit please apply!","description_format":"text","description_chars":5842,"description_truncated":false,"requirements":{"experience_years_min":7,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["AI for Science","Scientific & Lab Software"],"lifecycle":[{"event":"open","at":"2026-09-10T23:08:53Z"}],"visa":[{"country":"US","licensed_sponsor":true,"evidence":"H-1B filings in 12 months: 3","filings_12m":3,"filings_prev_12m":0,"green_card_filings_12m":0,"median_offered_wage_usd":147500,"route":null,"cap_exempt":false,"checked_at":"2026-10-15T11:24:14+00:00","sources":["US Department of Labor: LCA disclosure data (H-1B, H-1B1, E-3)"],"filings_for_role_12m":2}],"liveness":{"score":5,"band":"cold","label":"Long shot","p_open":1,"p_active":0.186,"p_room":0.28,"age_days":267,"expected_fill_days":41,"reasons":["conf:3","stale_co","ghost","win:tail","crowd:"],"computed_at":"2026-10-29T05:49:05Z"},"pay":null,"html_url":"https://alion.io/job/albertinvent-staff-ml-ops-engineer","json_url":"https://alion.io/job/albertinvent-staff-ml-ops-engineer.json","meta":{"generated_at":"2026-10-29T07:00:42Z","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":10679,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-30T00:00:00Z"}},"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":669012},"rest":"https://alion.io/mcp/rest/get_company?id=669012"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Falbertinvent-staff-ml-ops-engineer"},{"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%2Falbertinvent-staff-ml-ops-engineer"},{"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%2Falbertinvent-staff-ml-ops-engineer"},{"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/albertinvent-staff-ml-ops-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Falbertinvent-staff-ml-ops-engineer"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":677953}},{"tool":"search_jobs","arguments":{"company":"albertinvent.com","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":677953},"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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