{"id":26499,"url":"https://alion.io/job/sensmore-ml-ops-data-engineer-robotics","title":"ML Ops / Data Engineer - Robotics","company":{"id":7112,"name":"Sensmore","domain":"sensmore.com","url":"https://alion.io/company/sensmore","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"A","score":95,"open_postings":11,"ghost_share":0,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":153,"computed_at":"2026-10-03T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Potsdam, Germany","Berlin, Germany"],"countries":["DE"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":80000,"max_usd":182000,"period":"year","method":"role_seniority_country_cell","sample_n":8},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":true,"technologies":[{"name":"Amazon Redshift","optional":false},{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"BigQuery","optional":false},{"name":"Delta Lake","optional":false},{"name":"Embodied AI","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GCP","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Kubeflow","optional":false},{"name":"MLFlow","optional":false},{"name":"Physical AI","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"Vision-Language-Action","optional":false},{"name":"CI/CD","optional":true},{"name":"CloudFormation","optional":true},{"name":"Kubernetes","optional":true},{"name":"Terraform","optional":true}],"status":"live","first_seen_at":"2026-03-06T15:54:26Z","employer_posted_date":"2026-03-06","last_verified_at":"2026-10-04T01:37:26Z","board_verified":true,"closed_at":null,"days_open":211,"trust":{"level":"ok","repost_count":1,"flags":["company_stale"],"days_open":210},"description":"sensmore is a Berlin/Potsdam-based robotics startup delivering production-proven automation for industries where the world’s raw materials are extracted, moved, and processed. Its automation system transforms heavy machines into intelligent, automated robots powered by Physical AI and vertically integrates them into the full production environment: from the machine and safety infrastructure to network infrastructure, site processes, and operational interfaces.\nCo-developed with customers, sensmore is backed by Point Nine Capital, leading industry investors, the State of Brandenburg, and the European Union.\nRole Overview:\nAs our Data Engineer, you will design, build, and maintain the data infrastructure that powers Sensmore’s embodied AI and Vision-Language-Action Models (VLAMs). You’ll collaborate with Robotics, ML and Software engineers to ensure clean, reliable data flows from our sensor arrays (radar, LiDAR, cameras, IMUs) into training and inference pipelines. This role blends classic data engineering (ETL/ELT, warehouse design, monitoring) with ML Ops best practices: model versioning, data drift detection, and automated retraining.\nKey Responsibilities:\nBuild & operate data pipelines: Ingest, process, and transform multi-sensor telemetry (radar point-clouds, video frames, log streams) into analytics-ready and ML-ready formats.\n\nDesign scalable storage: Architect high-throughput, low-latency data lakes and warehouses (e.g., S3, Delta Lake, Redshift/Snowflake).\n\nEnable ML Ops workflows: Integrate DVC or MLflow, automate model training/retraining triggers, track data/model lineage.\n\nEnsure data quality: Implement validation, monitoring, and alerting to catch anomalies and schema changes early.\n\nCollaborate cross-functionally: Partner with Embedded Systems, Robotics, and Software teams to align on data schemas, APIs, and real-time requirements.\n\nOptimize performance: Tune distributed processing, queries, and storage layouts for cost-efficiency and throughput.\n\nDocument & evangelize: Maintain clear documentation for data schemas, pipeline architectures, and ML Ops practices to uplift the whole team.\n\nRequired Qualifications:\n3+ years of hands-on experience building production data pipelines in the cloud (AWS, GCP, or Azure).\n\nProficiency in Python, SQL, and at least one big-data framework.\n\nFamiliarity with ML Ops tooling: DVC, MLflow, Kubeflow, or similar.\n\nExperience designing and operating data warehouses/data lakes (e.g., Redshift, Snowflake, BigQuery, Delta Lake).\n\nStrong understanding of distributed systems, data serialization (Parquet, Avro), and batch vs. streaming paradigms.\n\nExcellent problem-solving skills and the ability to work in ambiguous, fast-paced environments.\n\nPreferred Skills:\nBackground in robotics or sensor data (radar, LiDAR, camera pipelines).\n\nKnowledge of real-time data processing and edge-computing constraints.\n\nExperience with infrastructure as code (Terraform, CloudFormation) and CI/CD for data workflows.\n\nFamiliarity with Kubernetes and containerized deployments.\n\nExposure to vision-language or action-planning ML models.\n\nWhat We Offer:\nBuild physical AI for the world's largest off-highway machinery - making them intelligent, safe, and ready for every tough task\n\nJoin the pioneer in intelligent robotics backed by Point Nine & other Tier 1 investors\n\nCombine cutting-edge robotics research in end-to-end learning & Vision Language Action Model with real-world heavy mobile equipment\n\nTailor your own career path, whether you like to become technical specialist or technical team lead\n\nExperience a great team culture, beverages, and an amazing office environment\n\nBenefits:\nAttractive compensation package and stock options.\n\nBeverages on-site and regular social events.\n\nEngage with top-tier researchers, engineers, and thought leaders.\n\nInfluence the future of robotic technologies and tackle significant technological challenges.\n\nAssistance with relocation to Berlin.\n\nAbout Us:\nHeavy machinery, light years ahead.\nsensmore automates the world's largest machines with unprecedented intelligence. Our proprietary Physical AI enables heavy machines such as wheel loaders to instantly adapt to dynamic environments and execute new tasks without prior training.\nWe integrate cutting-edge robotics into a platform powering intelligence and automation products - transforming productivity and safety for customers in mining, construction, and adjacent industries today.\nWe are proudly backed by Point Nine and other Tier 1 investors.","description_format":"text","description_chars":4521,"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":["Stock options"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":true,"industries":["Robotics AI","Industrial AI"],"lifecycle":[{"event":"open","at":"2026-03-06T15:54:26Z"},{"event":"close","at":"2026-08-13T11:25:55Z"},{"event":"reopen","at":"2026-08-29T23:50:16Z"}],"visa":[],"liveness":{"score":23,"band":"cold","label":"Long shot","p_open":1,"p_active":0.532,"p_room":0.44,"age_days":210,"expected_fill_days":153,"reasons":["conf:11","win:tail","crowd:"],"computed_at":"2026-10-03T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/sensmore-ml-ops-data-engineer-robotics","json_url":"https://alion.io/job/sensmore-ml-ops-data-engineer-robotics.json","meta":{"generated_at":"2026-10-04T02:48:41Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":4193,"day_limit":5000,"remaining_today":807,"minute_limit":60,"resets_at":"2026-10-05T00:00:00Z"}}}