Remote ML Ops Engineer: Scalable AI Infrastructure Lead

CyberCoders; United States; Remote; USD 162,000 - 198,000; Full time

Benefits offered by this job

Medical/Dental/Vision

401K with 40% match up to first 6%

PTO, Holidays, Personal Days, Service/

Job summary

CyberCoders is seeking an experienced ML Ops Engineer to build and scale the infrastructure, automation, and operational processes that support production machine learning and AI systems. This role partners with Data Science, Data Engineering and Product teams to ensure models are deployed, monitored, governed, and continuously improved in a secure, regulated environment.

Healthcare experience and HIPAA compliance are highly desired. Fully remote with East Coast/Central hours flexibility.

Qualifications

• Master's degree in Computer Science, Software Engineering, or related field.
• 7+ years in DevOps, Data Engineering, ML Engineering, or related disciplines.
• 4+ years supporting production machine learning systems and model operations.
• Healthcare/HIPAA experience in regulated environments preferred.
• Strong deployment, observability, governance and platform engineering knowledge.

Responsibilities

• Build and maintain end-to-end ML pipelines for training, validation, deployment and monitoring.
• Manage model lifecycle: versioning, promotion, deployment and retirement.
• Design scalable real-time and batch model serving infrastructure using API, containers and cloud-native tech.
• Develop feature store, data versioning and training-serving consistency solutions.
• Support generative AI and LLM apps, including RAG, prompt management and usage monitoring.
• Monitor model drift, latency, and pipeline health; establish CI/CD and CT workflows.
• Automate provisioning, security controls, secrets management and compliance processes.
• Collaborate with Data Science, Engineering and Product teams to improve reliability, governance and ops excellence.
• Provide technical leadership and mentorship on MLOps best practices.

Skills

DevOps

Data Engineering

ML Engineering

Strong communicator

Detail-oriented

REST APIs

Event-driven architectures

Distributed systems

Python

Bash

SQL

Go

Java

AI governance

Education

Master's degree in Computer Science or related

Tools

Docker

Kubernetes

EKS

Terraform

AWS CloudFormation

MLflow

Databricks

SageMaker

Bedrock

S3

Lambda

API Gateway

DynamoDB

Redshift

Athena

Glue

Step Functions

Kinesis

Secrets Manager

Kafka

Kinesis streaming

Delta Lake

Unity Catalog

Job description

CyberCoders is seeking an experienced ML Ops Engineer to build and scale the infrastructure, automation, and operational processes that support production machine learning and AI systems. This role partners with Data Science, Data Engineering and Product teams to ensure models are deployed, monitored, governed, and continuously improved in a secure, regulated environment.

Healthcare experience and HIPAA compliance are highly desired. Fully remote with East Coast/Central hours flexibility.