Senior Machine Learning Engineer

Metropolis is an artificial intelligence company that uses computer vision technology to enable frictionless, checkout-free experiences in the real world. We are reimagining parking so that millions of consumers can just 'drive in and drive out.' Our vision is to empower people to transact in the real world with speed, ease, and convenience that is unparalleled, even online. Tomorrow, we will power checkout-free experiences anywhere you go, enhancing the everyday experiences of living, working, and playing – giving us back our most valuable asset, time.

Metropolis is seeking a Senior Machine Learning Engineer to play a crucial role in developing innovative pricing algorithms tailored to various parking scenarios. The responsibilities include translating complex real-world problems into well-defined mathematical objectives and constraints, and implementing large-scale optimization algorithms critical for the success of this role. The right candidate will possess a robust background in optimization, forecasting, and causal inference, particularly as it relates to pricing applications.

You will be involved in every stage of the ML development pipeline, from data acquisition and ingestion to analysis, prototyping, and deployment. We are looking for someone who thrives in an entrepreneurial setting, collaborates effectively in a fast-paced environment, and is willing to break new technological ground at Metropolis.

Responsibilities:

• Research and develop optimization, machine learning, and statistical models to tackle complex pricing challenges.
• Navigate large and complex datasets to derive insights that inform key algorithmic strategies for pricing.
• Shepherd models and algorithms from conception to production, ensuring successful and sustainable deployments.
• Communicate ideas and results effectively to both technical and non-technical audiences.
• Collaborate closely with cross-functional teams to ensure alignment with organizational objectives and requirements.

Requirements and Qualifications:

• PhD (strongly preferred) or MS in Operations Research, Statistics, Economics, Computer Science, or a relevant quantitative discipline.
• 4+ years of industry experience as a ML scientist, research engineer, or in an equivalent role.
• Strong proficiency in Python and SQL for model development and statistical analysis.
• Proven expertise in implementing and deploying machine learning algorithms related to optimization and forecasting.
• Experience with large-scale datasets, data warehouses, ETL pipelines, and familiarity with relevant tools and libraries.
• Proficiency with optimization libraries such as SciPy, CVXPY, or Gurobi, and cloud platforms such as AWS, Azure, or GCP.
• Previous experience in innovative, high-growth environments.
• Track record of publications in machine learning or optimization conferences and journals (e.g., ICML, ICLR, Neurips, INFORMS, SIAM, etc.).

When you join Metropolis, you’ll become part of a world-class team of product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to foster an inclusive culture where everyone has a voice and the best idea wins. Your role will be key in maintaining this culture as our organization grows.

The anticipated base salary for this position ranges from $170,000.00 to $210,000.00 annually. Actual salary offered will be determined based on various factors, including the applicant's qualifications, relevant experience, distinctive skills, education level, certifications, and location. The base salary is one component of Metropolis’s total compensation package, which may include healthcare benefits, a 401(k) plan, disability coverage, life insurance, stock options, bonus plans, and more.

Join us in making a difference as we build our future. Metropolis is an equal opportunity employer, dedicated to diversity, equality, and inclusion. We provide equal employment opportunities to all employees and applicants for employment, prohibiting discrimination and harassment of any type, regardless of race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.