Staff MLOps Engineer

TriNet; Atlanta (GA); On-site; USD 125,000 - 275,000; Full time

Benefits offered by this job

Medical, dental, and vision plans

Life and disability insurance

401(K) savings plan

Employee stock purchase plan

PTO and a comprehensive leave program

Job summary

A leading HR outsourcing provider is looking for a Staff MLOps Engineer to design and manage the infrastructure for efficient machine learning model deployments. This role involves collaboration with data scientists and engineers, focusing on CI/CD practices and monitoring systems to ensure model performance. Candidates should have at least 8 years of experience in MLOps or DevOps and proficiency in Python or Java. Located in Atlanta, this position offers a competitive salary between $125,000 and $275,000, along with comprehensive benefits.

Qualifications

• Typically 8+ years of experience in MLOps or DevOps roles.
• Experience with programming languages such as Python or Java.
• Strong knowledge of machine learning framework operations.

Responsibilities

• Develop and scale infrastructure for efficient ML model deployment.
• Design automation pipelines integrating CI/CD practices.
• Monitor and optimize deployed ML models to ensure efficiency.

Skills

MLOps

Python

Java

TensorFlow

PyTorch

Docker

Kubernetes

AWS

Azure

GCP

Education

Bachelor's Degree in Computer Science/Engineering or equivalent experience

Tools

Git

CI/CD tools

Tableau

Job description

Job Overview

As a Staff MLOps Engineer, you will play a pivotal role in designing, implementing, and optimizing machine learning operations within our infrastructure. You will collaborate closely with data scientists, software engineers, and other cross‑functional teams to ensure the seamless deployment and maintenance of machine learning models.

What you will do

• Develop, manage, and scale the infrastructure required for efficient and reliable machine learning model deployment, including orchestration, version control, and monitoring systems.
• Design and implement automation pipelines for model training, testing, validation, and deployment, integrating CI/CD practices to ensure smooth and consistent delivery of ML models.
• Deploy machine learning models into production environments, establishing monitoring and alerting systems to track model performance, health, and data drift. Proactively troubleshoot issues and optimize model efficiency.
• Collaborate with data scientists, software engineers, and DevOps teams to streamline the integration of machine learning solutions into existing software systems and workflows.
• Ensure adherence to security protocols and compliance standards throughout the machine learning lifecycle, implementing best practices for data privacy and model governance.
• Stay updated with the latest advancements in MLOps tools, technologies, and methodologies, and propose enhancements to existing processes to improve efficiency and reliability.
• Solve complex and ambitious problems by crafting elegant and impactful solutions.
• ontributes to technical innovations along with defining coding standards
• entors and support other members of the software development team and contribute to the software development best practices.
• Performs other duties as assigned
• Complies with all policies and standards

Education Qualifications

• Bachelor's Degree in Computer Science/Engineering or equivalent experience preferred

Experience Qualifications

• Typically 8+ years Proven experience working in a similar MLOps or DevOps role within a technical engineering environment. required
• Typically 8+ years Experience with programming languages such as Python, Java, or similar, along with experience with relevant ML frameworks (TensorFlow, PyTorch, etc.). required
• Experience with CI/CD pipelines, version control systems (Git), and automation tools.

Skills and Abilities

• Knowledge of end-to-end SDLC process in EDW, Data Lake, BI & MLOps projects
• Dimensional Modeling and Data warehouse, ODS concepts, such as star schemas, snowflakes, and normalized data models
• Strong knowledge of containerization technologies (Docker, Kubernetes) and cloud platforms (AWS, Azure, GCP).
• Ability to coordinate effectively with on-site and offshore resources through Managed Service Providers & IT Teams
• Knowledge of Reporting tools like Tableau is desired
• Excellent verbal and written communication skills
• Strong Problem-solving and organizational skills and ability to work in a fast-paced, collaborative environment.
• Solid understanding of machine learning concepts, model development, and deployment strategies.

Travel Requirements

Minimal

Work Environment

• Work in clean, pleasant, and comfortable office or home setting. The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job. Reasonable accommodations may be made to enable persons with disabilities to perform the essential functions.

Compensation and Benefits

The preferred location for this role is Atlanta, GA, and the salary range for this location is $125,000.00 to $275,000.00. All qualified external applicants will be considered for an in‑office role, based in Atlanta. All qualified internal candidates are encouraged to apply and consider relocation to Atlanta and may be considered for remote hire at the company’s discretion. The candidate’s final salary offer will be based on the candidate’s skills, education, work location and experience.

A candidate’s compensation may also include bonuses consistent with TriNet’s corporate bonus plan.

Additionally, subject to applicable eligibility requirements, TriNet offers permanent full-time employees a variety of benefits including medical, dental, and vision plans, life and disability insurance, a 401(K) savings plan, an employee stock purchase plan, eleven (11) Company observed holidays, PTO and a comprehensive leave program. For detailed information about our benefits offerings: https://www.trinet.com/documents/blt5b61a1040aae1904

Equal Opportunity Statement

TriNet is an Equal Opportunity Employer and does not discriminate against applicants based on race, religion, color, disability, medical condition, legally protected genetic information, national origin, gender, sexual orientation, marital status, gender identity or expression, sex (including pregnancy, childbirth or related medical conditions), age, veteran status or other legally protected characteristics. Any applicant with a mental or physical disability who requires an accommodation during the application process should contact [e-mail] to request such an accommodation.