Staff Machine Learning Engineer
$220,000–$280,000 year
On-siteAtlanta, Georgia, United States
Job Summary
Architect scalable ML systems by transitioning experimental Data Science models into robust, high-availability production services and steering low-latency inference design to serve decisions in milliseconds. Build scalable logging and data pipelines with Data Science to create a centralized feature store for training complex models across diverse domains. Champion MLOps best practices by implementing automated retraining pipelines and observability tools to ensure data drift and model degradation are caught instantly. Lead architecture decisions for consumer applications while managing the full ML lifecycle using tools like MLFlow, Kubeflow, and Databricks.
Required Qualifications
- 7+ years of experience in Machine Learning Engineering or Backend Engineering
- Proven track record of deploying and maintaining complex ML models in high-traffic production environments
- 3+ years of technical leadership
- Acting as a lead and driving architecture decisions for consumer applications or scalable backend platforms
- Proficiency in streaming architectures (Kafka/Flink/PubSub)
- Building low-latency services to serve model inference in <100ms
- Deep experience managing the full ML lifecycle (training, deploying, monitoring)
- Experience using tools like MLFlow, Kubeflow, Databricks, or SageMaker
- Expert in Python and SQL
- Deep experience with GCP services (BigQuery, Cloud Functions, GKE, Vertex AI) or AWS equivalents
- Must be authorized to work for any employer in the U.S.
- Willingness to relocate to Atlanta or work remotely within the U.S.
Desired Qualifications
- Experience implementing reinforcement learning or complex probabilistic models for dynamic pricing, risk management, or fraud detection
- Background in Daily Fantasy Sports (DFS), oddsmaking, or high-frequency trading
- Experience building and scaling 'Feature Stores' that successfully bridge batch historical data with real-time event streams
- Proficiency in Go, C++, or Rust for building high-performance inference layers
Hiring someone like this?
Get your role in front of qualified candidates on Sorce.