AI/Machine Learning Engineer

Role Overview

Senior Machine Learning Engineer for an AI-driven SaaS / Enterprise ML team, building production-grade ML systems for U.S. customers. This fully remote role works end-to-end across model development, deployment, and observability to deliver scalable, low-latency ML services.

Responsibilities

• Design, implement, and productionize ML models and pipelines for supervised and unsupervised learning with reproducible training and predictable inference
• Build and maintain model-serving infrastructure using REST/gRPC with containerization to meet latency, throughput, and cost targets
• Develop CI/CD, automated retraining, and canary / A-B rollout strategies
• Implement monitoring for model performance, drift detection, and data quality
• Optimize model architecture and inference using techniques like quantization, batching, and sharding to meet operational SLAs
• Collaborate with Data Scientists, Product, and Platform teams to convert ML prototypes into reliable microservices and data pipelines
• Document architectures, establish best practices for reproducibility, observability, and security, and mentor junior engineers

Requirements

• Strong Python expertise
• PyTorch and/or TensorFlow
• scikit-learn
• SQL
• Docker
• AWS
• MLOps experience

Preferred

• Hugging Face Transformers
• Kubernetes
• MLflow

Work Setup

• Fully remote (U.S.) with flexible schedules and asynchronous collaboration
• Ownership-focused, measurable-impact engineering culture