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Senior Data Engineer, Machine Learning
4 months ago
Locations: Los Angeles, California OR Seattle, WA
The Company
Metropolis is an artificial intelligence company that uses computer vision technology to enable frictionless, checkout-free experiences in the real world. Today, we are reimagining parking to enable millions of consumers to just "drive in and drive out." We envision a future where people transact in the real world with a speed, ease and convenience that is unparalleled, even online. Tomorrow, we will power checkout-free experiences anywhere you go to make the everyday experiences of living, working and playing remarkable - giving us back our most valuable asset, time.
The Role
Metropolis is seeking a Senior Data Engineer, Machine Learning to play a crucial role in architecting, implementing, and managing our ML data ecosystem to support advanced machine learning initiatives. You will be a thoughtful hands-on leader who operates based on principles and establishes best practices. While you are expected to be adept at making technical decisions, your responsibility is beyond just implementation – you will be influencing strategic decisions, mentoring engineers around you, and elevating the team through examples.
Responsibilities
- Design, build, and maintain robust, scalable data pipelines that support ML model development and deployment.
- Ensure efficient data storage, retrieval, and management practices that support real-time and batch processing needs.
- Work closely with ML engineers and data scientists to understand their data requirements and implement solutions that enable effective ML model training and evaluation.
- Develop and enforce policies for data quality, security, and compliance, ensuring integrity.
- Monitor and optimize the performance of data pipelines and key metrics to ensure efficient operation in production environments.
- Stay ahead of emerging technologies and methodologies in data engineering and machine learning.
- Mentor junior team members and elevate the team through knowledge sharing.
Requirements and Qualifications
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- Minimum of 5 years of experience in a Data Engineering role, with at least 2 years focused on ML data engineering.
- Proven experience in designing and implementing large-scale data pipelines and architectures.
- Strong programming skills in Python or Scala and proficiency with SQL.
- Experience building batch and streaming ingestion data pipelines for structured and unstructured data (text, images).
- Experience with data warehousing solutions (Snowflake, Databricks), feature stores, ETL tools (Airflow, Mage AI, DBT etc), and data modeling practices.
- Experience with big data technologies (e.g., Hadoop, Spark) and cloud services (e.g., AWS, Azure, Google Cloud Platform).
- Excellent problem-solving, analytical, and communication skills.
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 $140,000.00 to 190,000.00 hourly. 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.
