{"id":3813795,"url":"https://alion.io/job/viking-cruises-machine-learning-engineer","title":"Machine Learning Engineer","company":{"id":1787981,"name":"Viking Cruises","domain":"vikingcruises.com","url":"https://alion.io/company/vikingcruises-com","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Los Angeles, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":180000,"max":220000,"currency":"USD","period":"year","gross":null,"usd_annual":220000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"A/B Testing","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Feature Store","optional":false},{"name":"Git","optional":false},{"name":"LightGBM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false},{"name":"XGBoost","optional":false}],"status":"closed","first_seen_at":"2026-11-05T13:44:20Z","employer_posted_date":null,"last_verified_at":"2026-11-05T21:20:50Z","board_verified":false,"closed_at":"2026-11-05T21:20:50Z","days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"description":"Viking is hiring a Machine Learning Engineer to design, productionize, deploy, and operate machine learning solutions that support management decisions. The role focuses on translating experimental models into scalable, reliable, governed production systems on Databricks, with practical MLOps and measurable business outcomes.\n\nResponsibilities\nDesign, build, deploy, and maintain production-grade machine learning solutions supporting demand forecasting, dynamic pricing, inventory optimization, and recommendation use cases\nPartner with data scientists to convert experimental notebooks and prototypes into modular, tested, repeatable training and inference pipelines\nBuild and maintain feature engineering, model-training, batch-scoring, and real-time inference workflows using Python, Spark, SQL, Databricks, and MLflow\nImplement MLOps practices for experiment tracking, model registration and versioning, automated testing, CI/CD, controlled promotion, rollback, and reproducibility\nDefine and monitor model and operational health measures, including model quality, drift signals, latency, failures, data quality, resource utilization, and compute cost\nValidate model changes against reproducible datasets and established baselines, and assess downstream impact\nIntegrate model outputs with business applications and downstream platforms through reliable batch jobs, APIs, and secure data-access patterns\nOptimize model architecture, feature processing, training, and inference for scalability, reliability, maintainability, and cost efficiency\nImplement safeguards and fallback behavior so invalid data or failed optimization does not result in unsafe or misleading recommendations\nCollaborate with stakeholders to translate revenue-management requirements into technical specifications, acceptance criteria, and measurable outcomes\nCreate and maintain technical documentation, model cards, runbooks, deployment plans, monitoring procedures, and retraining and rollback strategies\nEnsure solutions comply with enterprise data governance, privacy, security, audit, and responsible AI requirements\n\nSkills\nBachelor's degree in Computer Science, Computer Engineering, Data Science, Statistics, Applied Mathematics, or a related field; or equivalent practical experience\n4+ years of relevant experience in machine learning engineering, applied data science, data engineering, or software engineering for production ML systems\nStrong proficiency in Python and SQL, including experience building maintainable, testable production code\nHands-on experience developing, deploying, and supporting machine learning models in production environments\nExperience with cloud platforms\nExperience with Apache Spark or Databricks and large-scale data processing\nKnowledge of supervised learning, forecasting, optimization, feature engineering, model evaluation, and experiment design\nExperience with software engineering practices including Git, code review, automated testing, CI/CD, configuration management, and environment promotion\nStrong problem-solving, critical-thinking, communication, and cross-functional collaboration skills\nAbility to work independently, manage changing priorities, and deliver in a fast-paced product environment\nMicrosoft Azure\nExperience designing batch and real-time model-serving patterns and integrating model outputs into operational applications\nExperience with model explainability techniques, statistical equivalence testing, A/B testing, and business-impact measurement\nExperience with Azure services such as Synapse Analytics, Event Hubs, Azure Data Lake Storage, or related integration services\nExperience with distributed ML libraries and frameworks such as scikit-learn, XGBoost, LightGBM, TensorFlow, PyTorch, or Spark MLlib\nExperience implementing governed feature stores, lineage, access controls, audit trails, and model approval workflows\n\nBenefits\nEmployees are eligible for annual discretionary bonus.\n401(k) plan with company match.\nEmployee Share Purchase Plan (ESPP) Viking full-time regular employees working in the United States can purchase Viking shares through payroll deductions.\nFull benefits including medical, dental, vision, life and disability insurance at a highly subsidized rate (some plans are fully paid by Viking).\nAccrue 15 paid vacation days, sick time accrual by state, and 6 paid holidays per year.\nOpportunity to take a free and/or discounted cruise.\nHighly subsidized gym membership.\nDiscounts on theatres, theme parks, movie tickets, travel discounts through IATA membership and too many more discounts to name.\nThis is a hybrid position based in our Woodland Hills, CA office, working from our office Monday and Thursday plus one additional weekday on a weekly basis.\n\nCompany Overview\nThank you for your interest in career opportunities at Viking. It was founded in 1997, and is headquartered in Basel, Basel-Stadt, CHE, with a workforce of 5001-10000 employees. Its website is https://www.vikingcruises.com.\n\nCompany H1B Sponsorship\nViking has a track record of offering H1B sponsorships, with 1 in 2022. 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