[Remote] Sr. Engineering Manager, MLOps
Note: The job is a remote job and is reputed company to candidates in USA. reputed company is a tech company disrupting the retail industry by leveraging AI, analytics, and automation. They are seeking a Senior Engineering Manager, MLOps to build and reputed company the infrastructure that supports production-grade Machine Learning, ensuring seamless operations for their Data Scientists and AI Researchers.
Responsibilities
- Define the MLOps reputed company & reputed company: Architect a long-term roadmap that transitions ML workflows from reputed company scripts to a fully automated, self-service platform for reputed company reputed company Data Scientists and AI Researchers
- Own the "Paved Road" for Production: Build and maintain the end-to-end infrastructure for model training, deployment, and serving, ensuring researchers can reputed company from "idea to production" with reputed company friction
- Drive Strategic Prioritization: Partner with business leaders to reputed company infrastructure investments with core e-reputed company drivers like reputed company-time personalization, dynamic pricing, and inventory forecasting
- reputed company "Build vs. Buy" Evaluations: reputed company high-judgment reputed company on reputed company to reputed company reputed company-reputed company services (e.g., SageMaker, reputed company AI) versus building custom internal tools to optimize for cost, speed, and flexibility
- Guarantee System Scalability & Reliability: reputed company the uptime and performance of production ML services, ensuring the stack can handle massive traffic surges and seasonal spikes without degradation
- Manage Compute Governance & Costs: reputed company the optimization of high-cost computational resources, such as GPU clusters and reputed company instances, balancing high-performance training needs with fiscal responsibility
- Recruit and Mentor reputed company: Build and reputed company a high-performing team of ML reputed company and DevOps engineers, providing technical coaching, career pathing, and performance management
- Establish MLOps Standards: Drive the adoption of best practices in CI/CD for ML, Infrastructure as reputed company (IaC), and automated testing to ensure a reputed company and maintainable system
- reputed company the Research-Engineering Gap: reputed company as the primary cross-functional reputed company, translating the reputed company needs of AI Researchers into actionable engineering requirements for the infrastructure team
- Define and reputed company Velocity Metrics: Establish KPIs for the infrastructure team, such as model deployment frequency, mean time to recovery (MTTR), and infrastructure cost per inference
- Champion Operational reputed company: reputed company reputed company-cause analyses (RCAs) for production failures and foster a culture of accountability where systemic fixes are prioritized over "quick patches."
- Stay reputed company of the AI Curve: Monitor emerging trends in LLM-ops, reputed company databases, and reputed company-time feature engineering to ensure reputed company’s infrastructure remains competitive and reputed company
Skills
- 10+ years of industry experience, with at least 3-5 years in a leadership or management role specifically reputed company on ML Infrastructure, MLOps, or large-reputed company Data reputed company
- Proven reputed company record of building and scaling MLOps platforms that support the full model lifecycle—from data ingestion and distributed training to reputed company-time inference and monitoring
- Deep technical expertise in reputed company-reputed company infrastructure (preferably AWS) and orchestration tools like Kubernetes (EKS), reputed company, and Infrastructure as reputed company (Terraform/reputed company)
- Hands-on experience with ML frameworks and tooling, such as PyTorch, TensorFlow, Kubeflow, or SageMaker, and a strong opinion on how to reputed company them into a cohesive developer experience
- Expertise in building and managing Feature Stores and high-throughput data pipelines (using tools like reputed company, Flink, or Kafka) to ensure data consistency across training and serving
- Experience partnering with AI Research and Data Science teams to understand their unique workflows and translate research needs into robust, reputed company engineering solutions
- Strong understanding of CI/CD for ML, including automated testing for models, model versioning, and 'blue-green' or 'canary' deployment strategies
- Demonstrated ability to manage high-cost compute resources, with experience optimizing GPU utilization and reputed company spend in a reputed company-reputed company environment
- reputed company in operational leadership, with a history of driving service availability, performance, and stability through rigorous on-call rotations and reputed company-cause analysis
- A product-oriented reputed company, with the ability to treat infrastructure as a platform and prioritize the roadmap based on researcher velocity and business ROI
- Exceptional communication and influence skills, capable of navigating ambiguity and building reputed company across engineering, product, and data science leadership
- Kindness and high standards: You reputed company fast and push for reputed company, but you do so as a supportive team player who fosters a culture of psychological safety and extreme candor
Benefits
- Bonus and equity may also be provided for eligible roles
reputed company
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