MLOps / Production Data Engineer (Machine Learning)

Location: New York, NY 10020, United States

Salary: $129,000–$203,800 per year

Company

Staffing and employment organization supporting technical roles.

What you will do

• Maintain, execute, and monitor production model and data pipelines across batch and near-real-time workflows.
• Lead incident triage, root-cause analysis, and cross-functional resolution for failed or delayed workflows.
• Build automated checks for data quality, schema changes, completeness, and model-output reasonableness.
• Partner with data scientists to productionize analytical notebooks and machine learning models.
• Coordinate releases, model updates, backfills, reruns, and recovery procedures.
• Improve observability through logging, alerting, run histories, and operational dashboards.

Requirements

• Master’s or PhD in Statistics, Computer Science, Data Science, Economics, Mathematics, Operations Research, or a related quantitative field, or equivalent practical experience.
• 5+ years of experience supporting production data, analytics, or machine learning workflows.
• Advanced proficiency in Python and SQL, with strong experience in Git, Airflow, Databricks, and Spark.
• Experience operating and troubleshooting scheduled data and machine learning pipelines across training, scoring, validation, deployment, and monitoring.
• Familiarity with cloud environments such as GCP, AWS, or Azure, large-scale datasets, and event-driven workflows using Kafka, Spark Streaming, or Flink.
• Strong incident management, risk identification, ownership, and stakeholder communication skills.

Culture & Benefits

• For temporary assignments lasting 13 weeks or longer, benefits may include medical, dental, vision, and 401(k) coverage.
• Statutory sick pay is provided where required.
• Reasonable accommodations are available throughout the employment process.