{"id":4256063,"url":"https://alion.io/job/expand-energy-sr-ml-ops-engineer","title":"Sr. ML Ops Engineer","company":{"id":2416309,"name":"Expand Energy","domain":"expandenergy.com","url":"https://alion.io/company/expandenergy","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","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":["Spring, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-11-05T08:00:00Z","employer_posted_date":"2026-11-05","last_verified_at":"2026-11-13T14:26:24Z","board_verified":true,"closed_at":null,"days_open":8,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":8},"description":"Our core values - Stewardship, Character, Collaborate, Learn, Disrupt - are the lens through which we evaluate every business decision. As a dynamic, growing company that offers extremely competitive compensation and benefits, our employees are our most valued assets and the foundation of Expand's performance among our E&P competitors.\nWe seek applicants from all backgrounds to ensure we get the best, most creative talent on our team. We realize that, historically, underrepresented groups feel the need to be 100% qualified in order to apply. If you meet any combination of our requirements, we encourage you to apply. We strive to hire people from a wide variety of backgrounds, not just because it’s the right thing to do, but because it makes our company stronger.\nJob Summary\nThis senior level position is responsible for building and operating the platforms, pipelines, and standards that support the development, deployment, and lifecycle management of machine learning models and data products. This role is expected to participate and lead communication with business customers as well as cross-functional IT staff, to support business teams delivering machine learning models and advanced analytics solutions.\nJob Duties & Responsibilities\nCollaborate with cross-functional teams including Business Stakeholders, Business Analysts, Data Engineers, and other Software Engineers to identify and define requirements\nDesign, develop, and support machine learning operations (MLOps) platforms and tools in support of data science activities\nImplement and maintain automated pipelines supporting the development, deployment, and operation of machine learning models and data products, ensuring scalability, reliability, and efficiency\nDevelop and maintain documentation for platforms, pipelines, and operational processes\nParticipate in code reviews, testing, and deployment activities, adhering to SDLC best practices\nEvaluate and recommend tools, patterns, and process improvements to enhance machine learning and advanced analytics delivery\nCollaborate with peers to share knowledge, support team capability development, and promote consistent engineering and MLOps practices\nJob Specific Skills\nHigh proficiency in Python as a primary engineering language, with experience building, testing, and operating production systems supporting machine learning and analytics workloads\nHigh proficiency with SQL, and familiarity with Spark or other distributed data processing frameworks\nExperience establishing and operating a sustainable MLOps environment, including model deployment, pipeline automation, monitoring, and lifecycle management\nStrong software engineering fundamentals, including object-oriented design, unit testing, exception handling, and use of common design patterns\nExpertise in data modeling, data warehousing, and ETL/ELT processes supporting analytics and machine learning cases\nHands-on experience with cloud-based data platforms and architectures, including Snowflake and Databricks\nStrong knowledge of CI/CD, DevOps, and release management practices used to deploy and operate production data and machine learning solutions\nStrong knowledge of SDLC processes, including Agile methodologies\nExcellent problem-solving skills and ability to troubleshoot complex issues in live production environments\nStrong communication and collaboration skills, with the ability to work effectively in a team environment\nEducation\nMinimum: High school diploma or GED\nPreferred: Bachelor’s degree - 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