Lead ML Engineer

Experis-US; United States; Remote; USD 96,000 - 110,000; Full time

Benefits offered by this job

Medical and Prescription Drug Plans

Dental Plan

Vision Plan

Health Savings Account

Health Flexible Spending Account

Dependent Care Flexible Spending账户

Job summary

Kroger is seeking a Lead ML Engineer to join a remote team supporting search and recommender systems across the e-commerce ecosystem. Lead end-to-end ML system architecture, define reusable platform patterns, and drive production-ready pipelines with strong observability.

The role requires 6+ years in production ML, strong Python and Spark skills, and experience with TensorFlow/PyTorch. Cloud, Docker, Kubernetes, and CI/CD expertise are essential.

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or related quantitative field.
• 6+ years building and operating production ML systems with technical leadership across complex ML initiatives.
• Strong Python and distributed data processing skills, including Spark and large-scale data pipelines.
• Hands-on experience with deep learning frameworks (TensorFlow, PyTorch, Hugging Face, scikit-learn) and training pipelines for batch/online inference.
• Production engineering experience with cloud platforms (GCP or Azure), containerization/orchestration (Docker, Kubernetes), and CI/CD practices.

Responsibilities

• Own end-to-end ML system architecture for search and recommendation workloads, including data access, training, serving, and monitoring.
• Establish reusable platform patterns for scalable training, batch/real-time inference, deployment, testing, and continuous delivery.
• Lead modular training and inference pipelines with data loading, preprocessing, artifact management, and validation.
• Enable search and recommendation capabilities with appropriate serving strategies, APIs, and feature pipelines.
• Drive performance engineering and production readiness through profiling, load testing, capacity planning, and reliability practices.

Skills

Python

Distributed data processing

Technical leadership

Education

Bachelor's or Master's in CS/Engineering/Data Science

Tools

Spark

TensorFlow

PyTorch

Hugging Face

scikit-learn

Docker

Kubernetes

Job description

Our client, Kroger, is seeking a Lead ML Engineer to join their team for a remote Lead ML Engineer. As a Lead ML Engineer, you will be part of the ML Engineering organization supporting search and recommender systems across the e-commerce ecosystem. The ideal candidate will have hands-on experience building and operating production machine learning systems, the ability to define reusable ML engineering patterns across teams, and the drive to deliver production-ready architectures with strong observability and reliability.

Job Title: Lead ML Engineer Location: Remote Pay Range: $70-80

What's the Job?

• Own end-to-end ML system architecture for search and recommendation workloads, covering data/feature access, training, model artifacts, serving, integration, monitoring, and operational controls.
• Establish reusable platform patterns and shared components for scalable training, batch and real-time inference, deployment, performance optimization, testing, and continuous delivery.
• Lead implementation of modular training and inference pipelines, including data loading, preprocessing, artifact management, validation, and low-latency or high-throughput prediction.
• Enable search and recommendation capabilities by supporting retrieval, ranking, personalization, and recommendation models with appropriate serving strategies, APIs, feature pipelines, and system integrations.
• Drive performance engineering and production readiness through profiling, load testing, capacity planning, containerization/orchestration guidance, reliability practices, and incident diagnosis.

What's Needed?

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related quantitative field, or equivalent practical experience.
• 6+ years of experience building and operating production machine learning systems, including technical leadership across complex ML engineering initiatives.
• Strong Python and distributed data processing skills, including experience with Spark and large-scale data or feature pipelines.
• Hands-on experience with deep learning or machine learning frameworks such as TensorFlow, PyTorch, Hugging Face, scikit-learn, or comparable technologies, plus training pipelines and batch/online inference systems.
• Production engineering experience with cloud platforms (GCP or Azure), containerization and orchestration (Docker, Kubernetes), and software practices such as CI/CD, automated testing, version control, and code review.

What's in it for me?

• Lead technical direction for scalable ML training and inference patterns that support search and recommendation experiences.
• Deliver reusable architecture and reference implementations that internal teams can maintain and extend.
• Work across Data Science, platform, data, backend, and product partners to align on interfaces, dependencies, risks, and execution plans.
• Build production-ready systems with strong observability, governance, and reliability practices.
• Transfer knowledge through design reviews, documentation, and hands-on enablement so teams can sustain delivered capabilities.

Upon completion of waiting period consultants are eligible for:

• Medical and Prescription Drug Plans
• Dental Plan
• Vision Plan
• Health Savings Account
• Health Flexible Spending Account
• Dependent Care Flexible Spending Account
• Supplemental Life Insurance
• Short Term and Long Term Disability Insurance
• Business Travel Insurance
• 401(k), Plus Match
• Weekly Pay

About ManpowerGroup, Parent Company of:

• Manpower
• Experis
• Talent Solutions
• Jefferson Wells

ManpowerGroup® (NYSE: MAN), the leading global workforce solutions company, helps organizations transform in a fast-changing world of work by sourcing, assessing, developing, and managing the talent that enables them to win.

We develop innovative solutions for hundreds of thousands of organizations every year, providing them with skilled talent while finding meaningful, sustainable employment for millions of people across a wide range of industries and skills.

Our expert family of brands – Manpower, Experis, Talent Solutions, and Jefferson Wells – creates substantial value for candidates and clients across more than 75 countries and territories and has done so for over 70 years.

We are recognized consistently for our diversity – as a best place to work for Women, Inclusion, Equality and Disability and in 2023 ManpowerGroup was named one of the World's Most Ethical Companies for the 14th year – all confirming our position as the brand of choice for in-demand talent.