[Remote] Manager Machine Learning Engineering – Amazon Store
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Note: The job is a remote job and is open to candidates in USA. HCA Healthcare is a leading healthcare provider, and they are seeking a Manager of Machine Learning Engineering. The role involves leading the development and implementation of machine learning operations while building and managing a high-performing team of ML engineers to enhance ML delivery and standardization across the organization.
Responsibilities
- Build and lead high-performing team of ML Engineers, including hiring, coaching, and providing career development while fostering a culture of technical excellence and knowledge sharing.
- Actively contribute to MLOps assigned pod development through hands-on coding and technical implementation, leading by example through direct contribution to critical platform components and infrastructure when possible while ensuring pod priorities and technical challenges are addressed.
- Partner with Pod Tech Leads to ensure embedded engineers are delivering according to best practices and are following pod and platform standards.
- Collaborate with AI Platform leadership to inform technical standards and architectural patterns for AI platform, engineering best practices and standardization across pods.
- Drive platform adoption, engineering best practices and standardization across pods.
- Collaborate with other engineering leaders to implement and maintain technical standards while aligning teams around technical decisions.
- Conduct code reviews and participate in technical discussions to maintain high engineering standards and quality of platform usage and MLOps best practices across pods.
- Champion ML platform capabilities across product teams while identifying and addressing barriers to platform adoption, ensuring consistent implementation of platform patterns.
- Balance hands-on development with technical leadership and team management responsibilities to ensure successful and consistent platform usage.
- Collect and synthesize feedback from engineers and pod tech leads to inform platform priorities and roadmap based on pod needs.
- Create opportunities for technical growth and skills development for team members.
- Lead technical discussion and architecture review to promote platform-aligned solutions.
Skills
- Bachelor's degree - Required
- 1+ year(s) of experience in a leadership role - Required
- 7+ years of experience in software engineering with a focus on ML Engineering and AI - Required
- Current hands-on coding abilities with recent experience in ML/AI systems - Required
- Strong technical background in ML engineering with demonstrated coding expertise - Required
- Deep Python development expertise with a focus on ML systems - Required
- Strong understanding of Machine Learning workflows and operational requirements through direct implementation - Required
- Hands on experience implementing and scaling model CI/CD and Continuous Training pipelines - Required
- Hands on experience with modern Python development practices including typing, linting, test frameworks, and package management - Required
- Deep understanding of containerization and deployment of ML/AI models and systems - Required
- Strong background agile development within product teams - Required
- Understanding of ML Development Lifecycle management and MLOps best practices - Required
- Experience managing team of embedded engineers distributed across product teams - Required
- Understanding of ML Monitoring and observability - Required
- Master's degree - Preferred
- Engineering or platform engineering - Preferred
- Experience with LLMs and Infrastructure - Preferred
- Experience integrating with feature stores - Preferred
- Deep understanding of ML/AI system unit testing, integration testing, and load testing - Preferred
- Experience with Distributed model training - Preferred
- Hands on experience with Kubeflow, Argo, MLFlow or other ML/AI Training orchestrators - Preferred
- Hands on experience and knowledge of ML/AI metadata tools - Preferred
- Deep hands-on experience with Terraform or other IaC tools - Preferred
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