IT Services - Lead Machine Learning Operations Engineer (MLOps)

Fugetec; Chicago (IL); Hybrid; USD 140,000 - 190,000; Full time

Job summary

Fugetec in Chicago, IL (Remote) is seeking a Lead Machine Learning Operations Engineer to lead and optimize ML workloads, focusing on scalable, reliable development and deployment.

You will collaborate with data scientists, implement automated ML workflows, design CI/CD pipelines for models, and ensure robust serving, monitoring, and performance.

The role requires 10+ years of experience, strong Python/Go skills, and deep knowledge of AWS, Docker, Kubernetes, and ML frameworks.

Qualifications

• Bachelor’s/Master’s in Computer Science or related field.
• 3+ years in MLOps or DevOps.
• Strong Python/Go skills, CI/CD experience, and AWS proficiency.
• Knowledge of Docker, Kubernetes, AWS CDK, and CloudFormation.

Responsibilities

• Architect and deploy scalable ML solutions in AWS.
• Design CI/CD pipelines for ML workflows.
• Collaborate on model serving, versioning, and monitoring.
• Automate tasks to improve workflow efficiency.
• Stay updated on MLOps tools and practices.

Skills

MLOps

CI/CD

Python

Go

TensorFlow

PyTorch

AWS proficiency

Education

Bachelor’s/Master’s in Computer Science or related field

Tools

Docker

Kubernetes

AWS CDK

CloudFormation

Job description

Lead Machine Learning Operations Engineer (MLOps)

Chicago, IL ( Remote )

Full Time

11-Nov-2024

Role: Lead Machine Learning Operations Engineer (MLOps)

Location: Chicago, IL ( Remote )

Visa: Any visa is fine

Experience: 10+ years

Required Skills: MLOps, AWS Certified Machine Learning – Specialty, ML frameworks (TensorFlow, PyTorch)

Job Description:

We’re looking for a skilled MLOps Engineer to lead and optimize ML workloads, focusing on infrastructure for scalable, reliable ML development and deployment. You'll collaborate with data scientists, automate workflows, and ensure high model performance.

Responsibilities

• Architect and deploy scalable ML solutions in AWS


• Design CI/CD pipelines for ML workflows


• Collaborate on model serving, versioning, and monitoring


• Automate tasks to improve workflow efficiency


• Stay updated on MLOps tools and practices

Qualifications

• Bachelor’s/Master’s in Computer Science or related field


• 3+ years in MLOps or DevOps


• Strong Python/Go skills, CI/CD experience, and AWS proficiency


• Knowledge of Docker, Kubernetes, AWS CDK, and CloudFormation

Preferred

• Experience with MLflow, Tecton, AWS EMR