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Senior MLOps Engineer

3 months, 2 weeks ago
United States
Full-time
Senior
Machine Learning Engineer
Software Development
CI/CD Docker Encryption GCP Kubernetes Machine Learning MLOps Python Secrets Management Vertex AI
Apply Now
C the Signs

C the Signs

C the Signs is a cutting-edge cancer prediction system that uses artificial intelligence to enhance early detection and survival rates. The company is dedicated to reducing healthcare disparities by accelerating early cancer detection, improving patien...

Professional Services
51-250
Founded 2017
View All Jobs 8

Description

  • Design and operate ML platforms that support data ingestion, feature engineering, training, evaluation, deployment, and monitoring.
  • Build and maintain CI/CD pipelines for ML systems, including testing, packaging, versioning, reproducibility, automated rollbacks, and approvals.
  • Implement MLOps practices such as model registry, experiment tracking, lineage, governance, and reproducible training environments.
  • Develop scalable training infrastructure with distributed training, GPU scheduling, cost controls, and auto-scaling.
  • Create and maintain feature pipelines and feature stores to prevent training-serving skew and ensure consistency between training and inference.
  • Establish model monitoring and observability for performance, drift, fairness signals where relevant, latency, throughput, and data quality.
  • Build and own end-to-end LLM delivery pipelines, including prompt/versioning, retrieval, orchestration, evaluation, deployment, monitoring, and improvement.
  • Create LLM evaluation harnesses with offline and online testing, golden datasets, regression tests, human review workflows, and risk scoring.
  • Productionize ML models on GCP using containers and orchestration such as GKE or Cloud Run, with safe and reliable rollouts.
  • Design systems with security, privacy, governance, and compliance controls appropriate for healthcare data and workflows.

Requirements

  • 6+ years in software or platform engineering, including 4+ years operating ML systems in production or equivalent depth.
  • Strong experience in ML engineering, including training pipelines, evaluation, deployment patterns, monitoring, and iteration loops.
  • Strong engineering skills in Python and production-grade experience building APIs and services.
  • Demonstrated hands-on experience with LLM systems in production.
  • Strong experience with GCP services and cloud-native patterns.
  • Experience with Vertex AI, including pipelines, endpoints, feature store, model registry, and evaluation, and/or managed vector search on GCP.
  • Experience with containerization and orchestration tools such as Docker, Kubernetes/GKE, and/or Cloud Run.
  • Experience building observability for model or system health, including metrics, logs, tracing, dashboards, and alerting (preferred).
  • Experience with security, privacy, and governance practices for regulated or healthcare environments (preferred).

Benefits

  • Competitive salary and benefits package.
  • Flexible working arrangements, including remote or hybrid options.
  • Opportunity to work on life-changing AI technology that directly impacts patient outcomes.
  • A mission-driven team focused on improving health equity and saving lives.
  • Continuous learning opportunities with access to the latest tools and advancements in AI and healthcare.

Interested in this position?

Apply directly on the company website

Apply Now

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