{"id":1620767,"url":"https://alion.io/job/atoms-cloud-platform-ml-infrastructure-engineer","title":"Cloud Platform - ML Infrastructure Engineer","company":{"id":1533,"name":"Atoms","domain":"atoms.co","url":"https://alion.io/company/atoms","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"A","score":89,"open_postings":84,"ghost_share":0,"stale_share":0.25,"repost_share":0,"time_to_fill_p50_days":60,"computed_at":"2026-10-10T05:45:15Z"}},"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":["Pittsburgh, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":141000,"max_usd":280000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":383},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"Amazon SageMaker","optional":false},{"name":"Argo Workflows","optional":false},{"name":"CI/CD","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Kubeflow","optional":false},{"name":"MLFlow","optional":false},{"name":"Terraform","optional":false},{"name":"Kubernetes","optional":true}],"status":"live","first_seen_at":"2026-09-11T17:03:19Z","employer_posted_date":"2026-09-30","last_verified_at":"2026-10-10T22:36:59Z","board_verified":true,"closed_at":null,"days_open":29,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":29},"description":"Who we are \nLab37 Robotics, is a technology company focused on the development and deployment of robots designed specifically for direct-to-customer food production. Our mission is to revolutionize the food industry by creating innovative robotic solutions that enhance efficiency, quality, and customer satisfaction. We are passionate about pushing the boundaries of technology to deliver cutting-edge products that meet the evolving needs of our clients.\nWhat you'll do\nTake on ownership of the cloud platform infra layer that powers Lab37's robotics fleet. This spans building Cloud infra, ML, ETL, CI/CD pipelines that turn raw robot telemetry into actionable analytics, managing data discovery, data lineage and contributing to models training pipelines on our robots, and ensuring the observability and reliability of the entire data stack.\nWork with a small, high-impact platform team to build the systems that every product team at Lab37 consumes - from data scientists training models, to kitchen operations teams viewing dashboards, to engineers deploying new ML models to robots in the field.\nResponsibilities\nDesign, build, and maintain scalable ML infrastructure that abstracts away underlying storage, pipeline management, and repetitive environment setup tasks.\nImplement robust systems for automated model checkpointing, persistent metadata management, and experiment tracking across distributed training runs.\nCreate self-service ML workflows and tooling that empower ML engineers and data scientists to focus on core logic, model architecture, and validation.\nBuild and maintain automated ETL and data ingestion pipelines that stream and transform raw robot telemetry into clean datasets for training and analytics.\nContribute to infrastructure-as-code (Terraform) and CI/CD automation for model deployment, data processing, and cloud services.\nPartner with cloud and embedded engineers to streamline model deployment to fleets of robots in the field and participate in on-call rotations for platform reliability.\nMonitoring & Cost: Track model drift, system throughput, and optimize cloud compute costs.\nWhat we're looking for\n3+ years of experience in Cloud infrastructure, MLOps, and data engineering at scale.\nHands-on experience designing systems for automated model checkpointing, model registries, and metadata management (e.g., MLflow, Kubeflow etc).\nStrong experience with ML & Cloud workflow orchestration tools (SageMaker, K8, Argo Workflows, Bedrock) and cloud storage architectures.\nProven track record building self-service ML platforms, pipeline abstraction layers, or automated developer workflows.\nExperience with working with embedded engineers.\nWhy join us\nDemand for online food delivery is growing really fast! In the last 5 years, just in the US, the overall market has expanded 10X from $10B to $100B, and could expand to $500bn- $1T by 2030.\nChanging the restaurant industry: You’ll be part of a team that helps restaurants succeed in online food delivery. \nCollaborative environment: You will receive support and guidance from experienced colleagues and managers, helping you to learn, grow and achieve your goals, and you’ll work closely with other teams to ensure our customer’s success.\nWhat else you need to know\nThis role is based in our Pittsburgh office. As a company driven by invention and continuous change - we are constantly reimagining our industries, building new products, and refining how we operate. We do our best work together. That’s why all of our office-based teams work onsite, five days a week.\nThe base salary range for this role is$140,000 - $174,500 per year.\nActual compensation will be determined on an individual basis and may vary depending on experience, skills, and qualifications.\nBase salary is just one part of your total rewards package. You may also be eligible for equity awards and an annual performance-based bonus.\nBenefits Summary (USA Full-Time Exempt Employees):\nMedical, dental, and vision insurance (multiple plans, incl. HSA options).\nCompany-paid life and disability insurance (short- and long-term).\nVoluntary insurance: accident, critical illness, hospital indemnity.\nOptional supplemental life insurance for self, spouse, and children.\nPet insurance discount.\n401(k).\nHealth Savings Account (HSA)\nFlexible Spending Accounts (Healthcare, Dependent Care, Commuter)\nTime Off policies:\nDiscretionary vacation days\n8 paid holidays per year\nPaid sick time\nPaid Bereavement leave\nPaid Parental Leave\nBenefits are subject to change at the company's discretion.\nAtoms accepts applications on an ongoing basis.\nReady to join us as we serve those who serve others? \n#LI-Onsite","description_format":"text","description_chars":4660,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Equity","Life insurance","Parental leave","Vision insurance"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial Intelligence","Manufacturing","Robotics","Industrial Automation"],"lifecycle":[{"event":"open","at":"2026-10-01T20:44:01Z"}],"visa":[],"liveness":{"score":76,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.842,"p_room":0.9,"age_days":28,"expected_fill_days":60,"reasons":["conf:3","velocity","win:mid","comp:brand"],"computed_at":"2026-10-10T05:45:15Z"},"pay":null,"html_url":"https://alion.io/job/atoms-cloud-platform-ml-infrastructure-engineer","json_url":"https://alion.io/job/atoms-cloud-platform-ml-infrastructure-engineer.json","meta":{"generated_at":"2026-10-11T01:23:51Z","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","counted_by":"address","units_charged":1,"used_today":2074,"day_limit":5000,"remaining_today":2926,"minute_limit":60,"resets_at":"2026-10-12T00:00:00Z"}},"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":1533},"rest":"https://alion.io/mcp/rest/get_company?id=1533"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fatoms-cloud-platform-ml-infrastructure-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%2Fatoms-cloud-platform-ml-infrastructure-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%2Fatoms-cloud-platform-ml-infrastructure-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/atoms-cloud-platform-ml-infrastructure-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fatoms-cloud-platform-ml-infrastructure-engineer"}]}