{"id":943546,"url":"https://alion.io/job/align-technology-inc-ai-backend-engineer-mwd","title":"Machine Learning Backend Engineer / MLOps (AWS, Python, C#) (m/w/d)","company":{"id":678151,"name":"Align Technology","domain":"aligntech.com","url":"https://alion.io/company/align-tech","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Pinpoint","truth_index":{"grade":"A","score":100,"open_postings":10,"ghost_share":0,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":16,"computed_at":"2026-11-08T05:47:12Z"}},"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":["Darmstadt, Germany"],"countries":["DE"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon CloudWatch","optional":false},{"name":"Amazon EC2","optional":false},{"name":"Amazon S3","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"AWS","optional":false},{"name":"AWS Lambda","optional":false},{"name":"C#","optional":false},{"name":"CI/CD","optional":false},{"name":"Datadog","optional":false},{"name":"Docker","optional":false},{"name":"GitHub Actions","optional":false},{"name":"Jenkins","optional":false},{"name":"Kubernetes","optional":false},{"name":"Machine Learning","optional":false},{"name":"Prometheus","optional":false},{"name":"Python","optional":false},{"name":"Splunk","optional":false},{"name":"Terraform","optional":false}],"status":"live","first_seen_at":"2026-09-14T19:39:52Z","employer_posted_date":"2026-10-20","last_verified_at":"2026-11-08T23:45:16Z","board_verified":true,"closed_at":null,"days_open":55,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":55},"description":"Role summary\nThis position is ideal for a mid-level software engineer specializing in cloud-native backend development to join the exocad Machine Learning team as a Backend Engineer, owning the production services that put ML models in front of users. Working closely with ML researchers, frontend engineers, and product teams across sites, you'll extend and operate the model serving layer behind exocad's dental CAD workflows: inference APIs, deployment and rollout automation, versioning, monitoring, and the performance and cost tuning that keeps them healthy under real workloads. You'll also contribute to the upstream training and labeling infrastructure that feeds them. This role focuses on the engineering that turns research prototypes into reliable, observable, traceable production systems, and on the operational discipline that keeps model behavior predictable release over release.\n\nKey Responsibilities\nMaintain, extend, and operate the production services that serve exocad’s ML models as part of the exocad AI Design product.\nOwn model deployment end to end: containerized builds, versioning, staged rollout, rollback, and reproducible release artifacts.\nAutomate provisioning and deployment with Terraform and AWS-native tooling so environments stay consistent and releases repeatable.\nBuild monitoring into serving systems for latency, throughput, resource utilization, and error rates, and act on what the telemetry shows.\nCollaborate with engineering, and product teams to deliver compliant and business-aligned cloud and data solutions.\nOwn deployments in both our AWS global and AWS China environments, partnering with our regional experts on data residency requirements.\n\nSkills, Knowledge & Expertise\n\nEducation: Bachelor’s degree in Computer Science, Software Engineering, or a related field, or similar education.\nExperience: 4+ years in backend engineering, including 2+ years of hands-on experience designing and operating systems on AWS.\n Skills: Strong proficiency in Python, and C#; solid grounding in systems design and distributed systems; solid understanding of AWS services (SageMaker, EC2, Lambda, S3, CloudWatch, RDS); experience with infrastructure-as-code (Terraform) and CI/CD automation (Jenkins); hands-on experience with Docker and containerized services.\nCommunication: Ability to clearly document and explain technical concepts to diverse audiences.\nTeamwork: Proven ability to collaborate effectively across global, cross-functional teams.\n Product Mindset: Ability to understand what our customers really need and build accordingly.\nComplementary skills\nGeneral understanding of machine learning concepts, training and evaluation workflows.\nExperience with GitHub Actions.\nFamiliarity with Kubernetes, and container orchestration.\nExperience with monitoring, logging, and observability tools such as Splunk, Datadog, or Prometheus.\nJob Benefits\nExciting and varied tasks in a dynamic and growing software company\nFlat hierarchies and fast decision-making\nA positive working environment that values both freedom and responsibility\nStrong team spirit and a very pleasant atmosphere\nModern offices, workstations and the latest technologies\nFlexible working hours\nTraining and development opportunities\nCompany events\nSports activities and work-life balance initiatives\nFree drinks, fruit and snacks\nCanteen with in-house cook\nGood transport connections\nJobTicket / JobRad","description_format":"text","description_chars":3418,"description_truncated":false,"requirements":{"experience_years_min":4,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":["Company events","Flexible schedule","Sports activities"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Dental Products & Labs"],"lifecycle":[{"event":"open","at":"2026-09-15T19:39:52Z"}],"visa":[],"liveness":{"score":16,"band":"cold","label":"Long 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