Senior Manager, Machine Learning Engineering

10+ years of professional experience in data and machine learning engineering with proven expertise in building enterprise-scale, auditable ETL pipelines and data governance mechanisms

5+ years of experience in leadership and management, ideally having managed other managers

MS or PhD in computer science and/or a quantitative discipline

Strong experience in distributed data processing like Apache Spark, Kafka, Cloud native data storage and processing services

1+ years experience building data /eval pipelines and deploying agentic AI solutions (LLMs and/or VLMs)

Experience managing technical programs, defining milestones, and communicating progress to diverse audiences

Familiarity with deep learning frameworks such as TensorFlow or PyTorch

Strong proficiency with SQL and Python

Engage effectively with external data providers and vendors

Familiarity with computer vision systems and models (e.g. object detection, tracking, segmentation)

Manage large scale datasets and database tools for data processing

Deploy ML services to the cloud with a focus on scalability and reliability

Operate in innovative, high-growth environments

4 Days in Office: Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection

When you join Metropolis, you'll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. The anticipated base salary for this position is $200,000.00 USD to $250,000.00 USD annually. The actual base salary offered is determined by a number of variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base salary is one component of Metropolis’s total compensation package, which may also include access to or eligibility for healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans and more. #LI-AR1 #LI-Onsite

Metropolis may utilize an automated employment decision tool (AEDT) to assess or evaluate your candidacy for employment or promotion. AEDTs are used to assist in assessing a candidate’s application relative to the required job qualifications and responsibilities listed in the job posting.

As part of this process, Metropolis retains data relevant to your candidacy, including personal information, for a period that is reasonably necessary for the use of the tool. If you are hired for the position, your data may become part of your employee records.

Metropolis Technologies is an equal opportunity employer. We make all hiring decisions based on merit, qualifications, and business needs, without regard to race, color, religion, sex (including gender identity, sexual orientation, or pregnancy), national origin, disability, veteran status, or any other protected characteristic under federal, state, or local law.