Senior MLOps Engineer

Business Unit/Group: WBD Studio Economics

Requisition Number: 30691-1

Intended Start Date: 2/24/2026

Contract Duration: 10-months

Possibility For Extension / Conversion? Possible

Max Hourly Pay Rate: $113.07/hr

OT Required / Expected? No

WB Games Resource(s)? No

CNN Resource(s)? No

Separation Specific (Y/N)? No

Post-Separation Entity: WB

What We Do/Project

We’re looking for a Senior MLOps Engineer to design, build, and operate scalable machine learning infrastructure in AWS. This role partners closely with Data Scientists and platform teams to productionize models, establish robust ML platforms, and ensure reliable, observable, and secure model lifecycle management. The ideal candidate brings strong software engineering fundamentals, deep AWS expertise, and a pragmatic approach to enabling data science teams to move quickly from experimentation to production. Experience building new ML infrastructure, vs operating inside of existing infrastructure, is a huge advantage.

Job Responsibilities / Typical Day in the Role

Enable production deployment of machine learning models

• Partner with Data Scientists to prepare development code for production deployment, including refactoring, packaging, standardization, and performance optimization
• Build and maintain CI/CD pipelines for model training, validation, and deployment
• Support batch and real-time inference workflows using scalable AWS-native services
• Develop and maintain model APIs to be integrated into user products

Build and operate core MLOps platform capabilities

• Design and implement a centralized model registry to track versions, metadata, lineage, and promotion stages
• Build and maintain a feature store to support consistent feature computation for training and inference
• Establish standardized ML pipelines for data ingestion, training, evaluation, deployment, and monitoring
• Define infrastructure-as-code patterns to provision and manage ML environments reliably

Ensure reliability, monitoring, and governance of ML systems

• Implement monitoring for model performance, data drift, and operational health
• Establish alerting and rollback strategies for production model failures
• Partner with security and platform teams to ensure compliance, access controls, and auditability

Collaborate across product, data, and platform teams

• Work closely with Data Scientists to align experimentation workflows with production constraints
• Collaborate with data engineers and architects to ensure feature availability, freshness, and quality
• Support agile product PODs by communicating API design and delivery for integration into user products

Must Have Skills / Requirements

1) Experience in MLOps, ML Engineering, or backend software engineering with ML systems

a. 4+ years of experience

2) Strong experience building and operating ML systems in AWS (e.g., SageMaker, ECS, Lambda, Step Functions, S3, IAM)

a. 4+ years of experience

3) Proficiency in Python and experience with ML frameworks and tooling used in production environments

a. 4+ years of experience

Nice to Have Skills / Preferred Requirements

1) None

Soft Skills

1) Strong understanding of the machine learning lifecycle and how data science workflows translate to production systems

2) Ability to collaborate effectively with Data Scientists and translate experimental work into robust production solutions

3) Strong communication skills and comfort working across technical and non-technical stakeholders

Technology Requirements

1) Strong experience building and operating ML systems in AWS (e.g., SageMaker, ECS, Lambda, Step Functions, S3, IAM)

2) Proficiency in Python and experience with ML frameworks and tooling used in production environments

3) Experience building APIs and backend services for model inference

4) Hands-on experience with CI/CD, infrastructure as code (e.g., Terraform, CloudFormation), and containerization

Education / Certifications

1) None required.

Interview Process / Next Steps

1) 1st round with HM and WBD Data Architect

2) 2nd round with Senior Manager

Additional Notes

• Sourcing in CA – Burbank
• Hybrid – schedule flexible

Please note that this is a contract role providing services to Warner Bros. Discovery through external staffing partners of Allegis Global Solutions. If you are selected for this role, you will be employed by AGS and will not be an employee of Warner Bros. Discovery.

This role is eligible for the following benefits

• Medical, dental & vision
• Hospital plans
• 401(k) Retirement Plan – Pre-tax and Roth post-tax contributions available
• Life Insurance (Company paid Basic Life and AD&D as well as voluntary Life & AD&D for the employee and dependents)
• Company paid short and long-term disability
• Health & Dependent Care Spending Accounts (HSA & DCFSA)
• Employee Assistance Program
• Time Off/Leave(PTO, Allegis Group Paid Family Leave, Parental Leave

Benefits are subject to change and may be subject to specific elections, plan, or program terms.

AGS is an Equal Opportunity Employer and will consider all applications without regard to race, sex, age, color, religion, national origin, veteran status, disability, sexual orientation, gender identity, genetic information or any characteristic protected by law.

If you would like to request a reasonable accommodation, such as the modification or adjustment of the job application process or interviewing process due to a disability, please email [email protected] for other accommodation options.

In accordance with the Immigration Reform and Control Act of 1986, employment is contingent upon verification of identity and authorization to work in the United States. All persons hired will be required to complete Form I-9 and provide acceptable documentation as required by law.

Please note that we may use artificial intelligence (AI) tools to screen, assess, or select applicants for this position. These tools may analyze application materials and assist our team in identifying candidates whose qualifications best match the requirements of the role. If you have questions about our use of AI in the hiring process, or would like more information, please contact us.

• We reserve the right to pay above or below the posted wage based on factors unrelated to protected classifications.

Individual compensation offered for this position within this range will depend on many factors, including qualifications, skills, relevant experience, job knowledge, geographic location, internal equity, and other pertinent job-related factors.

San Francisco Candidates only: Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

City of Los Angeles Candidates only: We will consider for employment all qualified applicants, including those with criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the City of Los Angeles’ Fair Chance Initiative for Hiring.