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Senior Machine Learning Ops Engineer Jobs (NOW HIRING)

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Senior Machine Learning Engineer

New York, NY

$114K - $157K/yr

Sr. Machine Learning Engineer Location: New York, NY Sponsorship: Yes Relocation: Yes Industry: Machine Learning A leading provider of AI is looking for a Sr. ML Engineer. Our client is an industry ...

Hirekeyz Inc

Sr. Machine Learning Engineer

Fort Belvoir, VA · On-site

$118K - $162K/yr

Role: Sr. Machine Learning Engineer Location: Ft. Belvoir, VA (On-site with Hybrid Option) Duration: Long Term Contract Clearance: DOD Top Secret Clearance (Must) As a consultant, will be working to ...

Button, Inc.

Senior Machine Learning Engineer

$153K - $198K/yr

As a Senior Machine Learning Engineer, you will own the end to end ML lifecycle at Button, from the data and feature pipelines that feed models, through training and evaluation workflows, to ...

Leidos

Senior Machine Learning Engineer

Vista, CA · On-site

$107K - $195K/yr

We are seeking a Senior Machine Learning Engineer to work on MLOPS that support the testing, and release of object detection algorithms for our portfolio of products that help safeguard the flow of ...

Leidos

Senior Machine Learning Engineer

Vista, CA · On-site

$107K - $195K/yr

We are seeking a Senior Machine Learning Engineer to work on MLOPS that support the testing, and release of object detection algorithms for our portfolio of products that help safeguard the flow of ...

Adobe Systems

Senior Machine Learning Engineer

San Jose, CA · On-site

$122K - $168K/yr

Senior Machine Learning Engineer Agent Platform - Adobe Experience Platform THE OPPORTUNITY Build ... ML-Ops or Agent-Ops experience . You've built eval frameworks, execution tracing, drift detection ...

BE Group

Senior Machine Learning Engineer

Malvern, PA · On-site

$120K - $158K/yr

We are assisting our client in hiring for a Senior Machine Learning Engineer. Our client is an established SaaS company serving banks, credit unions, and fintechs. Their cloud-based platform helps ...

Adobe, Inc.

Senior Machine Learning Engineer

San Jose, CA · On-site

$122K - $168K/yr

Senior Machine Learning Engineer Agent Platform - Adobe Experience Platform THE OPPORTUNITY Build ... ML-Ops or Agent-Ops experience . You've built eval frameworks, execution tracing, drift detection ...

RIT Solutions, Inc.

Sr Machine Learning Engineer

Raleigh, NC · On-site

$101K - $139K/yr

RIT Solutions, Inc. is seeking a Senior Machine Learning Engineer. The role involves deploying machine learning models at scale and working with cloud services, Kubernetes, and orchestration of ...

Paradigm

WI · On-site

$120 - $180/hr

We are looking for a Senior ML Ops Engineer to be part of revolutionizing these industries. We are ... Deploy and support machine learning models and AI solutions in production, maintaining best ...

Rokt group

Senior Machine Learning Engineer

Austin, TX · On-site

$335 - $400/hr

We are hiring Senior Machine Learning Engineers We are hiring engineers with significant expertise in both machine learning and software engineering. You will be working with our engineering and ...

New

TEKsystems

Sr. Machine Learning Engineer

Menlo Park, CA · Hybrid

$70 - $85/hr

Senior Machine Learning Engineer (LLM Evaluation & AI Agents) Location: Menlo Park, CA (Hybrid) Employment Type: 6-Month Contract Compensation: $70.00-$85.00/hour (W-2) Help Advance the Next ...

The Marlin Alliance

Sr Machine Learning Engineer

San Diego, CA · On-site

$110K - $152K/yr

The Marlin Alliance, Inc. is seeking a talented and experienced Senior Machine Learning Engineer to join our team. The successful candidate will be expected to design, develop, and implement advanced ...

The Marlin Alliance

Sr Machine Learning Engineer

San Diego, CA · On-site

$110K - $152K/yr

The Marlin Alliance, Inc. is seekinga talented and experienced Senior Machine Learning Engineer to join our team. The successful candidate will be expected to design, develop, and implement advanced ...

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Senior Machine Learning Ops Engineer information

See salary details

$59.5K

$126.6K

$183.5K

How much do senior machine learning ops engineer jobs pay per year?

As of Aug 20, 2026, the average yearly pay for senior machine learning ops engineer in the United States is $126,557.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,500.00 and $143,500.00 per year, depending on experience, location, and employer.

What is a senior machine learning ops engineer?

Senior Machine Learning Ops (MLOps) Engineers are experienced professionals who design, build, and maintain the infrastructure and tools needed to deploy, monitor, and scale machine learning models in production environments. They work at the intersection of data science, software engineering, and DevOps to ensure ML models are robust, reliable, and secure. Their responsibilities often include automating model training pipelines, managing cloud resources, implementing CI/CD for ML, and ensuring model reproducibility. Senior MLOps Engineers also mentor junior staff and help define best practices for the organization’s ML workflow.

What are the key skills and qualifications needed to thrive as a senior machine learning ops engineer?

To thrive as a Senior Machine Learning Ops Engineer, you need expertise in machine learning, software engineering, cloud platforms, and experience with CI/CD pipelines, often supported by a computer science degree or equivalent experience. Proficiency with tools like Docker, Kubernetes, TensorFlow, PyTorch, and cloud services such as AWS, GCP, or Azure is typically required, along with familiarity with MLOps frameworks. Strong problem-solving, collaboration, and communication skills help you work effectively with cross-functional teams and manage complex ML model deployments. These skills are essential to ensure reliable, scalable, and efficient deployment of machine learning models in production environments.

What are some common challenges faced by senior machine learning ops engineers when deploying models to production?

Senior Machine Learning Ops Engineers often encounter challenges such as ensuring model reproducibility, managing model versioning, and automating deployment pipelines for scalability. Another key challenge is monitoring model performance and data drift in production, which requires robust logging and alerting systems. Collaborating closely with data scientists, software engineers, and IT teams is essential to address these challenges and maintain a stable, efficient ML infrastructure.

What is the difference between Senior Machine Learning Ops Engineer vs Data Engineer?

AspectSenior Machine Learning Ops EngineerData Engineer
CredentialsExperience with ML frameworks, cloud platforms, scripting, and DevOps toolsStrong SQL, ETL, database, and programming skills, often with cloud experience
Work EnvironmentFocus on deploying, monitoring, and maintaining ML models in productionDesigning and building data pipelines and infrastructure for data processing
Industry UsageCommon in AI/ML-focused companies, tech firms, and data-driven organizationsWidespread across industries for data management and analytics

While both roles involve working with data and cloud platforms, the Senior Machine Learning Ops Engineer specializes in deploying and maintaining machine learning models, whereas the Data Engineer focuses on building data pipelines and infrastructure. Understanding these distinctions helps in choosing the right career path or job search focus.

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Senior Machine Learning Ops Engineer jobs near you
Infographic showing various Senior Machine Learning Ops Engineer job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 23% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $126,557 per year, or $60.8 per hour.

Machine Learning Engineering Senior Engineer

Megan soft Inc

Dearborn, MI • On-site

$96K - $131K/yr

Contractor

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

Job Title: ML Ops Engineer
Location: Dearborn, MI (Hybrid – 4 Days/Week Onsite)
Duration: 12 Months
 
 
Note Only W2 Only USC,GC,H4EAD,GCEAD
 
Position Overview
We are seeking an experienced ML Ops Engineer to design, build, and optimize scalable machine learning data pipelines on Google Cloud Platform (GCP). The ideal candidate will have strong expertise in MLOps, Data Engineering, DevOps, Cloud Infrastructure, and Machine Learning to support Ford's connected vehicle and AI/Agentic initiatives.
The role involves developing robust batch and streaming data pipelines, implementing enterprise data governance, maintaining cloud infrastructure, optimizing ML solutions, and collaborating with cross-functional teams to deliver high-quality data products.
Key Responsibilities
  • Design, develop, and maintain scalable ML data pipelines on Google Cloud Platform.
  • Build batch and streaming data pipelines for connected vehicle data.
  • Optimize ML solutions for performance, scalability, security, reliability, and cost.
  • Develop and maintain cloud infrastructure using Terraform and CI/CD pipelines.
  • Build and monitor production data pipelines while providing production support.
  • Implement enterprise data governance, data lineage, and data quality standards.
  • Collaborate with data scientists, AI engineers, and business stakeholders.
  • Enhance DevOps capabilities using GitHub, Tekton, Docker, and GitHub Actions.
  • Deliver software using Agile methodologies, Test-Driven Development (TDD), CI/CD, and DevOps best practices.
  • Resolve code quality issues using SonarQube, Checkmarx, FOSSA, and Cycode.
  • Design Microservices and REST APIs for scalable data processing.
  • Support AI Agentic initiatives and connected vehicle analytics.
  • Troubleshoot production issues and ensure SLA compliance.
  • Continuously improve data engineering solutions and cloud infrastructure.
Required Skills
  • Google Cloud Platform (GCP)
  • Machine Learning / MLOps
  • TensorFlow
  • Python
  • Java
  • Spark
  • SQL
  • Artificial Intelligence / AI
  • Data Governance
  • Data Architecture
  • Cloud Architecture
  • Apache Kafka
  • REST APIs
  • Microservices
  • Git / GitHub / GitHub Actions
  • Terraform
  • Tekton
  • Docker
  • Jira
  • Agile Software Development
  • Strong Technical Communication & Collaboration Skills
Preferred Skills
  • Telematics
  • Data Modeling
  • Cloud Infrastructure
  • Data Mining
  • Database Design
  • Troubleshooting & Problem Solving
  • Leadership / Mentoring Experience
Required Experience
  • Master's degree with 4+ years of experience, or Bachelor's degree with 6+ years of relevant experience.
  • 4+ years of Data Engineering and software product development experience.
  • Strong experience with at least three of the following:
    • Python
    • Java
    • Spark
    • Scala
    • SQL
  • 3+ years building cloud-based production data pipelines using:
    • Google BigQuery, Redshift, or Azure Synapse
    • Airflow
    • MySQL, PostgreSQL, or SQL Server
    • Apache Kafka or GCP Pub/Sub
    • Microservices
    • REST APIs
    • Terraform
    • Docker
    • GitHub Actions
    • Tekton
    • Atlassian Jira
Preferred Experience
  • Ph.D. in Computer Science, Software Engineering, Information Systems, or related field.
  • 2+ years of ML Model Development and/or MLOps experience.
  • Experience with cloud architecture and application migrations.
  • GCP Professional Certifications.
  • Experience contributing to open-source projects.
  • Strong analytics and data profiling skills.
  • Experience implementing end-to-end automation across ML pipelines.
  • Excellent communication and stakeholder management skills.
  • Experience mentoring junior engineers.
Education
Required: Bachelor's Degree in Computer Science, Software Engineering, Information Systems, Data Engineering, or related field.
Preferred: Master's Degree or Ph.D.