{"id":2003967,"url":"https://alion.io/job/atos-ai-mlops-engineer","title":"AI / MLOps Engineer","company":{"id":3006,"name":"Atos","domain":"atos.net","url":"https://alion.io/company/atos","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","truth_index":{"grade":"A","score":99,"open_postings":4,"ghost_share":0,"stale_share":0.25,"repost_share":0,"time_to_fill_p50_days":17,"computed_at":"2026-10-17T05:46:00Z"}},"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":["Bydgoszcz, Poland"],"countries":["PL"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":47000,"max_usd":95000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":12},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Docker","optional":false},{"name":"GCP","optional":false},{"name":"Kubernetes","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"AI Agents","optional":true},{"name":"Apache Kafka","optional":true},{"name":"Edge AI","optional":true},{"name":"Grafana","optional":true},{"name":"Kubeflow","optional":true},{"name":"MLFlow","optional":true},{"name":"Prometheus","optional":true},{"name":"PyTorch","optional":true},{"name":"Scikit-learn","optional":true},{"name":"Spark","optional":true},{"name":"TensorFlow","optional":true},{"name":"Terraform","optional":true}],"status":"live","first_seen_at":"2026-10-03T02:00:00Z","employer_posted_date":"2026-10-03","last_verified_at":"2026-10-17T12:29:35Z","board_verified":true,"closed_at":null,"days_open":14,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":14},"description":"Atos is the Atos Group brand dedicated to AI-powered, secure, end-to-end digital services. Atos designs, develops, and operates critical digital environments that drive performance, resilience and sovereignty, helping public and private organizations worldwide retain control over their data and infrastructures, while meeting regulatory requirements.\nWith more than 52,000 employees serving over 4,500 clients across 54 countries, Atos helps modernize core IT systems, accelerate cloud and data transformation, strengthen cybersecurity, and deliver secure digital workplace environments to support its clients, its employees and society. Atos also provides consulting and advisory services through its Atos Amplify brand.\nA trusted partner in operating complex and mission-critical environments, Atos supports organizations across highly regulated and sovereign contexts.\nAbout Atos Group\nAtos Group is a global leader in digital transformation with c. 54,000 employees and annual revenue of c. €7.2 billion, operating in 54 countries under two brands - Atos for services and Eviden for products and systems. European number one in cybersecurity and a leader in cloud, Atos Group is committed to a secure and decarbonized future and provides tailored AI-powered, end-to-end solutions for all industries. Atos Group is listed on Euronext Paris.\nBuild, automte and scale enterprise AI solutions.\nWe are looking for an experienced AI / MLOps Engineer to help design, deploy and operate production-grade AI platforms and machine learning solutions.\nIf you are passionate about Machine Learning, Cloud technologies, automation and modern AI operations, we'd love to hear from you.\nKey Responsibilities\nDesign and implement scalable ML pipelines for training, deployment and monitoring\nAutomate data ingestion, preprocessing and feature engineering workflows\nIntegrate AI/ML models into enterprise applications and APIs\nDevelop and maintain CI/CD pipelines for Machine Learning systems\nMonitor model performance, detect drift and automate retraining processes\nDeploy AI workloads using Docker and Kubernetes\nEnsure security, compliance and operational excellence across AI services\nCollaborate closely with Data Scientists, DevOps Engineers and Software Developers\nRequired Skills\n3+ years of experience in AI/ML Engineering, MLOps or related roles\nStrong Python programming skills\nExperience deploying ML models into production environments\nHands-on experience with Azure, AWS or GCP\nKnowledge of Docker, Kubernetes and CI/CD practices\nExperience with monitoring and observability tools\nTechnologies We Use\nPython, TensorFlow, PyTorch, Scikit-Learn, MLflow, Kubeflow, Airflow, Docker, Kubernetes, Azure, AWS, GCP, Spark, Kafka, Terraform, Prometheus, Grafana\nNice to Have\nExperience with GenAI, LLMs or Agentic AI\nAI/Cloud certifications\nExperience working in large-scale enterprise environments\nWhy Join Us?\nWork with cutting-edge AI technologies\nBuild solutions used in real production environments\nCollaborate with international technology experts\nAccess learning, certification and professional development opportunities\nPlease note: Due to project requirements, applicants must hold citizenship of an EU Member State.\nHere at Atos, diversity and inclusion are embedded in our DNA. Read more about our commitment to a fair work environment for all.\nAtos is a recognized leader in its industry across Environment, Social and Governance (ESG) criteria. Find out more on our CSR commitment.\nChoose your future. 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