Senior Machine Learning Engineer, Operations Research

About Our Client:

The organization operates in the grocery delivery and fulfillment industry, addressing the challenge of providing reliable access to groceries and household goods. It supports a large customer base while creating flexible earning opportunities for personal shoppers. The organization continuously optimizes its fulfillment systems to improve operational efficiency, service quality, profitability, and shopper experience.

About the Opportunity:

The Senior Machine Learning Engineer, Operations Research applies machine learning, combinatorial optimization, and mathematical programming to solve complex fulfillment and marketplace challenges. This role designs and deploys advanced algorithms that improve order batching, shopper routing, service availability prediction, and real-time assignment. The position works closely with product, data science, engineering, and business teams to develop solutions that directly improve operational performance and shopper experience.

Responsibilities:

• Design, develop, and deploy machine learning solutions for complex marketplace and fulfillment challenges.

• Apply machine learning, combinatorial optimization, and mathematical programming techniques to improve operational processes.

• Develop algorithms for order batching, shopper routing, service availability prediction, and real-time assignment.

• Collaborate with product managers, data scientists, engineers, and other stakeholders to align ML solutions with business objectives.

• Engage with cross-functional partners to ensure successful integration and adoption of machine learning solutions.

• Analyze large datasets to identify opportunities for operational and marketplace improvements.

• Continuously evaluate and improve algorithms and models to enhance efficiency, scalability, and business outcomes.

Requirements:

• Master’s or PhD in Operations Research, Industrial Engineering, or a related quantitative field.

• Minimum 3 years of industry experience applying machine learning to large datasets.

• Strong programming skills in Python.

• Proficiency with SQL, Pandas, scikit-learn, XGBoost, and Keras/TensorFlow.

• Strong analytical, quantitative, and problem-solving skills.

• Ability to translate complex technical concepts into practical business solutions.

• Effective communication skills and ability to collaborate with stakeholders across organizational levels.

Preferred Qualifications:

• Knowledge of deep learning frameworks and methodologies.

• Experience applying machine learning and optimization techniques to marketplace, logistics, fulfillment, or other operational problems.

• Experience with large-scale optimization or real-time decision systems.

Pay Range and Compensation Package:

• Base pay range varies by location:

• California, New York, Connecticut, and New Jersey: $207,000–$218,500 USD.

• Washington: $198,000–$209,000 USD.

• Oregon, Delaware, Maine, Massachusetts, Maryland, New Hampshire, Rhode Island, Vermont, Washington, D.C., Pennsylvania, Virginia, Colorado, Texas, Illinois, and Hawaii: $190,000–$205,000 USD.

• All other states: $173,000–$182,500 USD.

• Eligible for new-hire equity grants and annual refresh grants.

• Final compensation may vary based on candidate experience, skills, qualifications, and location.

Benefits & Perks:

• Highly competitive compensation and benefits aligned with employee location.

Equal Opportunity Statement: Our client is an equal opportunity employer. They celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, or national origin.

Note:

TalentHop is not the Employer of Record (EOR) for this role. Our purpose in this opportunity is to connect exceptional candidates with leading employers. We help job seekers worldwide discover roles that match their goals and guide them to complete their full application directly through the hiring company’s career page or ATS.