Machine Learning Engineer

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Top Skills AWS MLOps (SageMaker, Lambda, Step Functions, S3) Python CI/CD Pipelines for Machine Learning Systems Production Machine Learning Deployments Model Monitoring, Observability, and Optimization Responsibilities Design, build, and maintain scalable machine learning pipelines supporting model training, deployment, and inference Develop and manage CI/CD pipelines for machine learning systems and deployment workflows Build Python-based tools and automation supporting ML operations and orchestration Implement monitoring, logging, alerting, and observability across production ML environments Collaborate with data scientists, cloud engineers, and application teams to productionize machine learning solutions Optimize infrastructure performance, reliability, security, and cloud spend across ML platforms Must Have Hands‑on AWS MLOps experience in production environments Strong experience with SageMaker, Lambda, Step Functions, and S3 Strong Python development experience for automation, orchestration, and pipeline development Experience building and supporting CI/CD pipelines for ML systems Proven experience deploying, monitoring, and maintaining machine learning models in production Strong troubleshooting skills across distributed cloud-based systems Nice to Have Infrastructure‑as‑Code experience (Terraform, CloudFormation, AWS CDK) Docker, ECS, or EKS experience Snowflake experience ML observability, model monitoring, or model versioning experience ML cost optimization and FinOps experience AWS certifications Why This Role Own end‑to‑end machine learning operations in a production environment Partner directly with data scientists and engineering teams on impactful AI initiatives Work with modern AWS technologies and cloud‑native ML infrastructure High visibility opportunity with direct business impact Contract‑to‑hire position with long‑term growth potential Experience Level : Mid‑Level Note : This posting is for an existing vacancy.

Company Benefits Medical, dental & vision Critical Illness, Accident, and Hospital 401(k) Retirement Plan – Pre‑tax and Roth post‑tax contributions available Life Insurance (Voluntary Life & AD&D for the employee and dependents) Short and long‑term disability Health Spending Account (HSA) Transportation benefits Employee Assistance Program Time Off/Leave (PTO, Vacation or Sick Leave) Application Deadline : This position is anticipated to close on Jul 16, 2026.

AI helps assess applications and qualifications, but final decisions are made by our hiring team. We are seeking an MLOps Engineer to build, deploy, and optimize machine learning infrastructure that supports scalable, secure, and production‑ready AI solutions in cloud environments.

Type : Contract-to-Hire (6-month initial engagement) Pay : $70-75 hr/w2 Location : San Diego, CA (Hybrid) IMPORTANT : Must be local to San Diego, CA Note : Unable to support f1, stem, h1b, c2c at this time.

Equality Statement : The company is an equal opportunity employer and will consider all applications without regards to race, sex, age, color, religion, national origin, veteran status, disability, sexual orientation, gender identity, genetic information or any characteristic protected by law.

San Francisco Fair Chance Ordinance : Pursuant to the San Francisco Fair Chance Ordinance, for all positions located in the city and county of San Francisco, we will consider for employment qualified applicants with arrest and conviction records.

Massachusetts Lie Detector : It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. Use of Artificial Intelligence (AI) : We may use Artificial Intelligence (AI) to support parts of our hiring process, including sourcing, screening, and evaluating candidates.

By applying, you acknowledge and agree that your application may be reviewed using AI tools. #J-18808-Ljbffr