Senior ML Engineering Leader, Production AI Data Pipelines

Metropolis; Washington (District of Columbia); On-site; USD 200,000 - 250,000; Full time

Benefits offered by this job

Healthcare

401(k) plan

Stock options

Bonus plans

Job summary

Metropolis is seeking a Senior Manager of Machine Learning Engineering in the Advanced Technologies Group to lead the technical vision and execution of foundational systems powering our AI. You will oversee data engineering, annotation pipelines, ML infrastructure, and deployment of agentic AI solutions to automate complex enterprise workflows.

You will build scalable data pipelines, manage ML tooling, productionize LLM/VLM solutions, and lead a team of data and ML infrastructure engineers.

Qualifications

• 10+ years in data and ML engineering with auditable ETL pipelines
• 5+ years in leadership, ideally managing other managers
• MS/PhD in CS or quantitative field
• Experience with Spark, Kafka, cloud data storage
• 1+ years building data/eval pipelines for agentic AI
• Experience managing technical programs and milestones
• Familiarity with TensorFlow or PyTorch
• Strong SQL and Python skills
• Experience with CV systems and models

Responsibilities

• Build scalable data infra for CV and AI pricing use cases
• Create data pipelines and annotation workflows
• Own MLOps lifecycle: training infra, model registries, low-latency inference
• Lead a high-performance data and ML infra team
• Productionize agentic AI, LLM/VLM solutions for workflows
• Develop data pipelines and feature stores for personalization/ads
• Collaborate with external vendors and ML leaders to align roadmaps

Skills

Leadership

SQL

Python

TensorFlow

PyTorch

Spark

Kafka

MLOps

LLMs/VLMs

Cloud platforms

Education

MS or PhD in Computer Science or quantitative discipline

Tools

Spark

Kafka

Cloud-native data services

LLM tooling

Job description

Metropolis is seeking a Senior Manager of Machine Learning Engineering in the Advanced Technologies Group to lead the technical vision and execution of foundational systems powering our AI. You will oversee data engineering, annotation pipelines, ML infrastructure, and deployment of agentic AI solutions to automate complex enterprise workflows.

You will build scalable data pipelines, manage ML tooling, productionize LLM/VLM solutions, and lead a team of data and ML infrastructure engineers.