Machine Learning Engineer

We need to output HTML fragment with sections: About the role? Actually we have Job Summary, Responsibilities, Requirements, Preferred Qualifications, What We Offer, About Viking. Also hybrid schedule info: hybrid position based in Woodland Hills, CA office, required to adhere to hybrid work policy, working from office Monday and Thursday plus one additional weekday weekly. That's schedule info. Also pay: Salary range $155,000 - $180,000 annually. Also benefits listed. We must not repeat job title as heading. Use

for section headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. But we should only include sections that have real specific content. We have content for About the role (maybe Job Summary). Responsibilities (Job Responsibilities). Requirements (Job Requirements). Preferred Qualifications (maybe Qualifications). Skills? Could be part of Requirements. Benefits (What We Offer). Pay (Salary range). Schedule (Hybrid work policy). About Viking (maybe About the company). The instructions list possible headings; we can use those that match. We must not include filler like "commensurate with experience". We have specific salary range, so Pay section is valid. Schedule: we have hybrid work policy details, so Schedule section valid. Benefits: we have list of benefits, so Benefits section valid. Qualifications: we have Requirements and Preferred Qualifications; we could combine into Requirements and Qualifications sections. The instruction says use headings like Requirements, Qualifications, Skills. We could have Requirements (mandatory) and Qualifications (preferred). Skills maybe not needed if covered. We must not repeat job title. Use

for each section heading. Use

• for any list of duties/requirements/benefits. Use

  for prose. We need to preserve all substantive information; do not invent or summarize away detail. Remove boilerplate like cookie/navigation/legal/EEO etc. There's none. We need to output only HTML fragment, no /, no markdown fences. Let's structure:

  About the role

  Job summary paragraph.

  Responsibilities

  • ... each responsibility as list item.

  Requirements

  • ... each requirement.

  Qualifications

  • ... preferred qualifications.

  Benefits

  • ... each benefit.

  Pay

  Salary range $155,000 - $180,000 annually...

  Schedule

  Hybrid position based in Woodland Hills, CA office. Required to adhere to hybrid work policy, working from office Monday and Thursday plus one additional weekday each week.

  Optionally

  About Viking

  with paragraph. But the instruction list didn't include About Viking but we can include if content exists. It says use headings e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. It didn't forbid other headings, but says "use

  for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule)." That suggests we can use those headings; we could also add About Viking but maybe not needed. However we should preserve all substantive information; the About Viking paragraph is substantive. We could include it under a heading like About the company or About Viking. Since not in list, maybe we can incorporate into About the role? But better to add a heading About Viking; it's still an h3. The instruction didn't forbid other headings, just gave examples. So we can include. We must not include duplicated lines. Ensure we capture all responsibilities verbatim? We should preserve but not invent. We'll copy each responsibility sentence as list item. Let's extract responsibilities from text: "Design, build, deploy, and maintain production-grade machine learning solutions supporting demand forecasting, dynamic pricing, inventory optimization, and recommendation use cases." "Partner with data scientists to convert experimental notebooks and prototypes into modular, tested, repeatable training and inference pipelines." "Build and maintain feature engineering, model-training, batch-scoring, and real-time inference workflows using Python, Spark, SQL, Databricks, and MLflow." "Implement MLOps practices for experiment tracking, model registration and versioning, automated testing, CI/CD, controlled promotion, rollback, and reproducibility." "Define and monitor model and operational health measures, including model quality, drift signals, latency, failures, data quality, resource utilization, and compute cost." "Validate model changes against reproducible datasets and established baselines, and assess downstream impact." "Integrate model outputs with business applications and downstream platforms through reliable batch jobs, APIs, and secure data-access patterns." "Optimize model architecture, feature processing, training, and inference for scalability, reliability, maintainability, and cost efficiency." "Implement safeguards and fallback behavior so invalid data or failed optimization does not result in unsafe or misleading recommendations." "Collaborate with stakeholders to translate revenue-management requirements into technical specifications, acceptance criteria, and measurable outcomes." "Create and maintain technical documentation, model cards, runbooks, deployment plans, monitoring procedures, and retraining and rollback strategies." "Ensure solutions comply with enterprise data governance, privacy, security, audit, and responsible AI requirements." That's 12 items. Requirements list: "Bachelor's degree in Computer Science, Computer Engineering, Data Science, Statistics, Applied Mathematics, or a related field; or equivalent practical experience." "4+ years of relevant experience in machine learning engineering, applied data science, data engineering, or software engineering for production ML systems." "Strong proficiency in Python and SQL, including experience building maintainable, testable production code." "Hands-on experience developing, deploying, and supporting machine learning models in production environments." "Experience with cloud platforms, with a preference for Microsoft Azure." "Experience with Apache Spark or Databricks and large-scale data processing." "Knowledge of supervised learning, forecasting, optimization, feature engineering, model evaluation, and experiment design." "Experience with software engineering practices including Git, code review, automated testing, CI/CD, configuration management, and environment promotion." "Strong problem-solving, critical-thinking, communication, and cross-functional collaboration skills." "Ability to work independently, manage changing priorities, and deliver in a fast-paced product environment." Preferred Qualifications list: "Experience designing batch and real-time model-serving patterns and integrating model outputs into operational applications." "Experience with model explainability techniques, statistical equivalence testing, A/B testing, and business-impact measurement." "Experience with Azure services such as Synapse Analytics, Event Hubs, Azure Data Lake Storage, or related integration services." "Experience with distributed ML libraries and frameworks such as scikit-learn, XGBoost, LightGBM, TensorFlow, PyTorch, or Spark MLlib." "Experience implementing governed feature stores, lineage, access controls, audit trails, and model approval workflows." Benefits list from "What We Offer You": "Highly competitive compensation plan." "Salary range $155,000 - $180,000 annually determined by a myriad of factors including, but not limited to, years of experience, depth of experience, and other relevant business considerations." "Employees are eligible for annual discretionary bonus." "401(k) plan with company match." "Employee Share Purchase Plan (ESPP) Viking full-time regular employees working in the United States can purchase Viking shares through payroll deductions." "Full benefits including medical, dental, vision, life and disability insurance at a highly subsidized rate (some plans are fully paid by Viking)." "Accrue 15 paid vacation days, sick time accrual by state, and 6 paid holidays per year." "Opportunity to take a free and/or discounted cruise." "Highly subsidized gym membership." "Discounts on theatres, theme parks, movie tickets, travel discounts through IATA membership and too many more discounts to name." "Viking is a certified Great Place to Work company. This certification is a result of our commitment to excellence, integrity and our teams’ outstanding contributions." But note salary range also appears in Pay section; we might not duplicate. In Benefits we could keep other benefits excluding salary range. However the instruction says preserve ALL substantive information; we can keep salary range in Pay section and also mention in Benefits? Might be duplicate. Better to keep salary range only in Pay section, and in Benefits list we exclude the salary range line. However the "What We Offer You" includes "Highly competitive compensation plan." and then salary range. We could keep "Highly competitive compensation plan." as a benefit item, and then Pay section gives range. That avoids duplication. Thus Benefits list items: - Highly competitive compensation plan. - Employees are eligible for annual discretionary bonus. - 401(k) plan with company match. - Employee Share Purchase Plan (ESPP) Viking full-time regular employees working in the United States can purchase Viking shares through payroll deductions. - Full benefits including medical, dental, vision, life and disability insurance at a highly subsidized rate (some plans are fully paid by Viking). - Accrue 15 paid vacation days, sick time accrual by state, and 6 paid holidays per year. - Opportunity to take a free and/or discounted cruise. - Highly subsidized gym membership. - Discounts on theatres, theme parks, movie tickets, travel discounts through IATA membership and too many more discounts to name. - Viking is a certified Great Place to Work company. This certification is a result of our commitment to excellence, integrity and our teams’ outstanding contributions. Pay section: Salary range $155,000 - $180,000 annually determined by a myriad of factors including, but not limited to, years of experience, depth of experience, and other relevant business considerations. Schedule section: Hybrid position based in our Woodland Hills, CA office. You will be required to adhere to our hybrid work policy, working from our office Monday and Thursday plus one additional weekday on a weekly basis. About Viking paragraph: Viking (NYSE: VIK) is a global leader in experiential travel with a fleet of more than 100 ships, exploring 21 rivers, five oceans and all seven continents. Designed for curious travelers with interests in science, history, culture and cuisine, Chairman and CEO Torstein Hagen often says Viking offers experiences For The Thinking Person™. Viking has more than 450 awards to its name, including being rated #1 for Rivers and #1 for Oceans five years in a row by Condé Nast Traveler in the 2025 Readers’ Choice Awards. Viking is also rated a “World’s Best” by Travel + Leisure—no other travel company has simultaneously received such honors by both publications. About the role paragraph: Job Summary We are seeking a highly motivated and experienced Machine Learning Engineer to join our dynamic and growing Data Platforms & Solutions team. As a Machine Learning Engineer at Viking you will design, productionize, deploy, and operate machine learning solutions that support management decisions. This role bridges data science, data engineering, and software engineering. You will work closely with data scientists, data engineers, analysts, product partners, and software developers to translate experimental models into scalable, reliable, governed production systems on Databricks. The position emphasizes practical MLOps, robust feature and training pipelines, reproducibility, observability, and measurable business outcomes. This is a hybrid position based in our Woodland Hills, CA office. You will be required to adhere to our hybrid work policy, working from our office Monday and Thursday plus one additional weekday on a weekly basis. But note we already have schedule info; we might not repeat hybrid details in About the role. However the About the role paragraph includes that sentence; we could keep it but it's duplicate with Schedule section. To avoid duplication, we could trim About the role to exclude the hybrid sentence, but we must preserve ALL substantive information; removing that sentence would lose info about hybrid. However we have it