Senior ML Engineer (lead) - remote

  • 41113
  • Non-Life - Data Science
  • |
  • United States
  • |
  • yesterday
RESPONSIBILITIES
  • · Lead ML engineering at the intersection of data science, data engineering, and MLOps.
  • · Build scalable pipelines, production ML models, and data products with real business impact.
  • · Work closely with product and business teams; mentor junior engineers and data scientists.
  • · Strong focus on unstructured data, LLMs, NLP, and modern ML workflows.
  • · Design and implement scalable ELT/ETL pipelines for analytics and ML systems.
  • · Build, validate, and deploy production ML models with CI/CD, versioning, retraining, and drift monitoring.
  • · Apply MLOps best practices for packaging, deployment, serving, and monitoring.
  • · Develop and maintain data models, feature stores, and governance standards.
  • · Deliver APIs, dashboards, notebooks, and apps that turn insights into business value.
  • · Own performance, reliability, and cost-efficiency of ML/data systems.
  • · Maintain observability: logging, alerting, lineage, SLOs, documentation.
  • · Partner with PMs and stakeholders to define requirements and drive adoption.
  • · Mentor data engineers/scientists and ensure clean handoffs to downstream teams.
QUALIFICATIONS
  • · 5+ years in ML engineering, data science, or data engineering.
  • · Strong Python + SQL
  • · Experience with Databricks / Snowflake / BigQuery or similar cloud warehouses.
  • · Hands-on with dbt, data modeling, and transformation frameworks.
  • · Skilled with scikit-learn, PyTorch, Transformers, and fine-tuning workflows.
  • · Proven MLOps experience: CI/CD, Kubernetes/serverless, MLflow, Ray Serve, etc.
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  • ->SALARY: 200-240k
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