Lead Engineer, MLOps

Technical Lead Manager Machine Learning Operations

Location: United States
Employment Type: Full-time
Focus: MLOps ML Platform Data Science Infrastructure AI-Assisted Development Supply Chain Technology

About Our Client

Our client is building modern logistics infrastructure for the future of ecommerce.

Their platform helps brands and consumers create a better post-purchase experience by making shopping shipping delivery and returns more seamless. By combining next-generation technology with a vertically integrated logistics network our client gives ecommerce brands more control over the customer delivery experience and helps turn delivery into an extension of the brand.

The company supports millions of deliveries and partners with some of the most recognized consumer brands in the market. Their culture is high-performance merit-based and built for people who want to compete win make an impact and help build an enduring company.

About the Role

Our client is hiring a Technical Lead Manager Machine Learning Operations to own the Data Science platform and lead the roadmap for building a more sophisticated stable and scalable ML infrastructure foundation.

This person will lead a team focused on ML infrastructure ML operations and embedded data science engineering. The team partners closely with data scientists to ensure forecasting network orchestration pricing routing and other machine learning systems are well-designed production-ready and built to scale.

This is a hands-on leadership role. Youll manage and grow the team while still contributing technically through architecture code design reviews roadmap ownership and setting the engineering bar.

What Youll Do

• Lead and grow a team of engineers across ML infrastructure MLOps and embedded data science project work

• Own the 12 year roadmap for improving the companys ML platform and operations research infrastructure

• Standardize and improve training infrastructure serving infrastructure deployment pipelines monitoring permissions environments and service operations

• Embed engineers into major science initiatives across forecasting network orchestration pricing routing and supply chain optimization

• Help ensure data science projects are production-ready from day one

• Build templates patterns and platform standards that help new ML systems get up and running quickly

• Partner closely with data science engineering developer experience and platform teams

• Drive adoption of AI-assisted and agentic development workflows across the Data Science organization

• Set standards for using AI in EDA model iteration ML/OR methodology and development velocity

• Review designs write code improve technical quality and raise the bar for production ML systems

• Participate in the on-call rotation for production data science systems

What Were Looking For

• Bachelors degree with 6 years of Machine Learning Engineering experience or Masters degree with 4 years of Machine Learning Engineering experience

• Experience leading or managing high-velocity ML platform MLOps or ML infrastructure teams

• Strong hands-on experience building production ML systems

• Experience with ML platforms including training infrastructure serving infrastructure feature stores orchestration monitoring and deployment pipelines

• Strong Python experience

• Experience driving AI-assisted or agentic tooling adoption inside an engineering or data science organization

• Strong knowledge of cloud-based data engineering and data science tools preferably AWS

• Experience with data warehouses such as Redshift Databricks Snowflake or similar platforms

• Experience with open-source large-scale ML tooling such as Ray Flink Feast or similar technologies

• Ability to balance short-term business impact with long-term platform vision

• Strong communication skills and a business-value-first approach to technical work

Bonus Experience

• Experience building ML systems in logistics ecommerce supply chain transportation marketplaces or operations-heavy businesses

• Experience supporting forecasting routing pricing network optimization or operations research systems

• Experience partnering directly with data science teams to productionize models

• Experience building reusable ML templates internal platforms or service creation frameworks

• Experience improving developer experience or AI-assisted development workflows

Why This Opportunity

• Lead the platform foundation behind high-impact data science systems

• Work on machine learning problems tied directly to real-world logistics delivery pricing forecasting and network orchestration

• Manage and grow a technical team while staying hands-on

• Own a meaningful roadmap for ML infrastructure at scale

• Help drive AI-assisted development adoption across a data science organization

• Build systems that power millions of package decisions and help major ecommerce brands deliver better customer experiences

• Join a high-performance team with strong growth potential and meaningful equity upside

Required Experience:

Senior IC