Director of Software Engineering – MLOps, ML Governance

Engineering ManagerEngineering ManagerFull TimeRemoteTeam 10,001+H1B SponsorCompany SiteLinkedIn

Location

United States

Posted

26 days ago

Salary

$138K - $200.1K / year

Bachelor Degree10 yrs expEnglishAWSAzureCloudDockerGoogle Cloud PlatformKubernetes

Job Description

• Leads the execution of deliverables with the risk and engineering teams ensuring projects are completed on time and within predefined requirements and budgets. • Accountable for team performance within assigned projects, including software engineering and MLOps initiatives. • Serves as subject matter expert on multiplatform applications and ML infrastructure, determining course of action under the direction of systems leadership. • Directs the system development lifecycle including the design, coding, testing, documentation, maintenance, and support of proprietary and purchased software systems and applications. • Leads the design, implementation, and scaling of enterprise MLOps platforms and capabilities, including CI/CD pipelines for ML, model versioning, automated testing, monitoring, and model lifecycle management. • Establishes best practices for model deployment, observability, performance monitoring, drift detection, and retraining strategies. • Partners with Data Science, Risk, Compliance, Legal, and Information Security teams to ensure machine learning systems meet regulatory, governance, and risk management requirements. • Implements and oversees ML governance frameworks including model documentation, validation, explainability, auditability, fairness/bias monitoring, and model risk management controls. • Ensures adherence to enterprise data governance, privacy, and AI risk policies, including responsible AI standards. • Recommends innovation and improvements to policy or procedures; has the latitude to make decisions affecting mid- to long-term operational results. • Develops long- and short-term business and technology strategies aligned to AI/ML roadmaps. • Responsible for managing operating costs and budgets, including infrastructure investments for ML platforms. • Makes decisions on pay, performance, appraisals, schedules, discipline, and hiring. • Builds and leads a high-performing MLOps and engineering organization, establishing clear career paths and leadership development for managers and senior engineers.

Job Requirements

  • Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field; or equivalent combination of professional experience and/or training required
  • 10+ years of experience in software engineering, including experience building distributed or cloud-based systems
  • 4+ years successfully managing teams (including managers), with demonstrated ability to develop, motivate, and direct leaders and technical contributors
  • Proven experience leading or building an MLOps function or production-grade ML platforms in an enterprise environment
  • Strong understanding of ML lifecycle management including model training, validation, deployment, monitoring, and governance
  • Experience implementing ML governance and model risk management frameworks (e.g., documentation standards, validation controls, bias/fairness testing, explainability techniques, audit readiness)
  • Familiarity with regulatory expectations for AI/ML in highly regulated industries (e.g., financial services, healthcare, etc., as applicable)
  • Experience with cloud platforms (AWS, Azure, GCP), containerization (Docker/Kubernetes), CI/CD pipelines, and infrastructure-as-code
  • Strong understanding of data governance, privacy, security, and compliance considerations related to AI/ML systems
  • Ability to manage a leadership pipeline by mentoring subordinate managers and nurturing senior technical talent
  • Excellent executive communication skills with the ability to translate complex ML and risk topics into business-aligned decisions.

Benefits

  • Medical, dental, vision and life insurance
  • Retirement savings – 401(k) plan with generous company matching contributions (up to 6%), financial advisory services, potential company discretionary contribution, and a broad investment lineup
  • Tuition reimbursement up to $5,250/year
  • Business-casual environment that includes the option to wear jeans
  • Generous paid time off upon hire – including a paid time off program plus ten paid company holidays and three floating holidays each calendar year
  • Paid volunteer time — 16 hours per calendar year
  • Leave of absence programs – including paid parental leave, paid short- and long-term disability, and Family and Medical Leave (FMLA)
  • Business Resource Groups (BRGs) – BRGs facilitate inclusion and collaboration across our business internally and throughout the communities where we live, work and play. BRGs are open to all.

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