ML Engineer, I - MLOps Framework

About Our Client

The organization operates in the grocery delivery sector, providing accessible delivery of groceries and household essentials to a large customer base. Through its technology-driven marketplace, it connects customers with personal shoppers while creating flexible earning opportunities and improving access to essential goods.

About the Opportunity

The Senior Machine Learning Engineer, Economist develops advanced machine learning systems that incorporate economic theory to address complex marketplace challenges. This role combines economics, econometrics, and machine learning to improve algorithms, optimize operational efficiency, and support data-driven business decisions. The position collaborates closely with product, engineering, data science, and economics teams to deliver scalable solutions with measurable business impact.

Responsibilities

• Design, develop, and deploy machine learning solutions that address economic and marketplace challenges.
• Apply economic theory, econometric methods, and machine learning techniques to complex business problems.
• Collaborate with product managers, data scientists, engineers, and economists to understand business needs and develop impactful solutions.
• Use observational and experimental data to evaluate causal relationships and inform marketplace decisions.
• Continuously improve algorithms and models to enhance operational efficiency and business outcomes.
• Translate complex analytical findings into actionable recommendations for cross-functional stakeholders.
• Share knowledge, methodologies, and best practices with the Economics team across different domains.
• Contribute to production deployment and ongoing improvement of machine learning systems.

Requirements

• Graduate degree (Master's or PhD) in Economics or a closely related field.
• Strong foundation in economic theory, applied econometrics, and quantitative business analysis.
• Experience applying causal inference methods to observational and experimental data.
• Knowledge of machine learning algorithms, modeling techniques, and evaluation methodologies.
• Proficiency in Python and data manipulation tools such as SQL and Pandas.
• Experience with machine learning libraries such as scikit-learn and XGBoost.
• Strong analytical, problem-solving, and quantitative skills.
• Excellent written and verbal communication skills.
• Self-motivated with strong ownership and ability to work independently.

Preferred Qualifications

• 1–3 years of industry experience for senior-level hires.
• Experience deploying machine learning models in production environments.
• Experience with cloud computing platforms and machine learning infrastructure.
• Experience applying economic or machine learning methods to marketplace optimization problems.
• Ability to collaborate effectively across technical and non-technical teams.

Pay Range and Compensation Package

• Base pay ranges vary by location, with listed ranges from $173,000–$218,500 USD annually.
• Eligible for new hire equity grants and annual refresh grants.
• Final offers vary based on experience, skills, qualifications, and location.