{"id":2314430,"url":"https://alion.io/job/danfoss-senior-engineer-mldata","title":"Senior Engineer, ML/Data","company":{"id":452335,"name":"Danfoss","domain":"danfoss.com","url":"https://alion.io/company/danfoss-6","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Career sitemap","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Sofia, Bulgaria"],"countries":["BG"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":36000,"max_usd":91000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":1986},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Dagster","optional":false},{"name":"Docker","optional":false},{"name":"GCP","optional":false},{"name":"Knowledge Graph","optional":false},{"name":"KServe","optional":false},{"name":"Kubernetes","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-10-12T03:22:17Z","employer_posted_date":"2026-10-12","last_verified_at":"2026-10-13T00:50:30Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"The Impact You'll Make\nDo you enjoy turning complex data into scalable solutions that enable smarter products and better decisions? Are you passionate about data engineering, machine learning and building production-ready AI capabilities? Then this could be the opportunity for you.\nAs our Senior Engineer, ML/Data, you’ll play a key role in building the data and AI foundation that supports advanced analytics and intelligent solutions across Danfoss Climate Solutions. Your work will help transform operational, sensor, product and business data into reliable, AI-ready data products and production machine learning workflows.\nWorking closely with data scientists, platform engineers and business teams, you’ll combine strong hands-on engineering skills with an MLOps mindset, helping us evolve toward a connected and scalable data ecosystem that enables energy optimization, predictive insights and smarter decision-making.\nWhat You’ll Be Doing\nDesign, build and maintain scalable data pipelines and ML-enabled data products, integrating sensor, device, product and business data into a reliable data platform\nDevelop and improve data ingestion, transformation and orchestration workflows using technologies such as Airflow, Mage or Dagster\nCollaborate with data scientists, engineers and domain experts to create high-quality, model-ready datasets and reusable foundations for analytics and AI use cases\nSupport the deployment, monitoring and operation of machine learning solutions in production, including KServe-based model serving and MLOps workflows\nBuild and improve automation for data quality, feature pipelines, model retraining and deployment, ensuring reliable and maintainable production workflows\nContribute to semantic data models and knowledge graph capabilities that enrich analytics and AI use cases across different business areas\nContinuously improve the scalability, observability, reliability and maintainability of our data and ML platform through automation and strong engineering practices\nWhat We're Looking For\nStrong hands-on experience in data engineering, machine learning engineering or similar roles, with solid Python and SQL skills\nExperience building and orchestrating production data pipelines using tools such as Airflow, Mage or Dagster\nExperience with cloud platforms such as Azure, AWS or GCP, together with Docker and Kubernetes\nGood understanding of MLOps, production model deployment and modern data architectures; experience with KServe is considered an advantage\nStrong problem-solving and collaboration skills, with the ability to work effectively across technical teams and stakeholders\nExperience with industrial IoT data, HVAC, energy systems, knowledge graphs or semantic data models is considered an advantage\nReady to Make a Difference?\nIf this role excites you, we’d love to hear from you! Apply now to start the conversation and learn more about where your career can go with us.\nOur Commitment to Transparency\nSalary ranges listed reflect only primary location and currency. For local salary ranges and specific benefits in your preferred hiring location, please ask your Talent Acquisition representative for more information.\nThe actual salary offer will carefully consider a wide range of factors, including your skills, qualifications, experience, and location. Any benefits listed do not promise or guarantee any particular benefit or specific action. They may depend on country or contract specifics and are subject to change at any time without prior notice.\nWant to know more? 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