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Senior Machine Learning Ops Engineer Jobs (NOW HIRING)

Adtech

ML Ops Engineer

Ashburn, VA · Hybrid

Adtech seeks a motivated, career and customer-oriented SME Machine Learning Ops Engineer . This is currently a hybrid position with two days onsite in Ashburn, VA and three days remote. In this role ...

RELX Group plc

Senior ML Ops Engineer

Philadelphia, PA

$112K - $179K/yr

Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global ... About the role, as a Senior Machine Learning Engineer you'll work on AI-based features (GenAI ...

RELX

Senior ML Ops Engineer

Atlanta, GA

$112K - $179K/yr

Are you a collaborative Machine Learning Ops Engineer looking to work for a mission driven global ... About the role, as a Senior Machine Learning Engineer you'll work on AI-based features (GenAI ...

Ascentt

Senior Machine Learning Engineer

Ann Arbor, MI

$102K - $140K/yr

Senior Machine Learning Engineer Ascentt is building cutting-edge data analytics & AI/ML solutions ... Strong knowledge of ML Ops practices including version control, model monitoring, and retraining ...

Ascentt

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $137K/yr

Senior Machine Learning Engineer Location: Ann Arbor, Michigan Experience Level: 7+ Years ... Strong knowledge of ML Ops practices including version control, model monitoring, and retraining ...

Moody's Analytics

MLOps Engineer

New York, NY · On-site +1

As the Machine Learning Ops Engineer for the AI Team you will: * Work closely with the Data Science ... Liaise with senior stakeholders across the Data function and the wider business * Use industry best ...

Ascentt

Senior Machine Learning Engineer

Plano, TX · On-site

$100K - $137K/yr

We are looking for an experienced Senior Machine Learning Engineer with deep expertise in ... Strong knowledge of ML Ops practices including version control, model monitoring, and retraining ...

Canopy

Senior Machine Learning Engineer

Detroit, MI

$95K - $131K/yr

Senior Machine Learning Engineer As a Senior Machine Learning Engineer within the AI Squad at Canopy and reporting to the Director of AI Engineering, you'll contribute to the development of cutting ...

The Marlin Alliance

Sr Machine Learning Engineer

Arlington, VA · On-site

$120K - $165K/yr

Senior Machine Learning Engineer 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 ...

Button

Senior Machine Learning Engineer

Manhattan, NY

$153K - $198K/yr

Senior Machine Learning Engineer Button's mission is to empower the companies shaping the creator and affiliate economy - fueling mobile growth with innovation and new paths to monetization. Today ...

The Marlin Alliance

Sr Machine Learning Engineer

Denver, CO

$107K - $147K/yr

Senior Machine Learning Engineer 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 ...

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Senior Machine Learning Ops Engineer information

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$59.5K

$126.6K

$183.5K

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

As of Jun 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 are the key skills and qualifications needed to thrive as a Senior Machine Learning Ops Engineer, and why are they important?

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.

What are Senior Machine Learning Ops Engineers?

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.
More about Senior Machine Learning Ops Engineer jobs
What cities are hiring for Senior Machine Learning Ops Engineer jobs? Cities with the most Senior Machine Learning Ops Engineer job openings:
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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 June 2026, with employment types broken down into 40% Full Time, 36% Part Time, 6% Temporary, 15% Contract, and 3% Nights. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $126,557 per year, or $60.8 per hour.
ML Ops Engineer

ML Ops Engineer

Adtech

Ashburn, VA • Hybrid

Other

Posted 5 days ago

Job description

Adtech seeks a motivated, career and customer-oriented SME Machine Learning Ops Engineer. This is currently a hybrid position with two days onsite in Ashburn, VA and three days remote.

In this role, you will collaborate within a cross-functional team to develop new Artificial Intelligence/Machine Learning (AI/ML) based solutions into operational pipelines to deliver mission impact for U.S. Customs and Border Protection (CBP). The ideal candidate will have deep expertise and experience with predictive modeling lifecycles, hands-on experience with machine learning tools and frameworks, and a pragmatic, customer-centric approach to applying ML models to solve complex problems.

Each day CBP oversees the massive flow of people, capital, and products that enter and depart the United States via air, land, sea, and cyberspace. The volume and complexity of both physical and virtual border crossings require the application of solutions to aid officers in detecting threats while promoting efficient trade and travel.

Title: SME Machine Learning Ops Engineer

Location: Ashburn, VA (Hybrid 2 days a week onsite)

Duration: Full time
 

Responsibilities include but are not limited to:

  • Lead the integration and deployment of trained AI/ML models into production environments (e.g., cloud, edge devices) using MLOps best practices
  • Develop and optimize model training & inference pipelines for real-time execution, and efficiently handle large-scale data processing
  • Work with data science teams to structure automated ML model health monitoring and refresh capabilities
  • Implement continuous integration, delivery and training (CI/CD/CT) workflows with commercial and open-source modeling platforms/services
  • Coordinate with Data Science and Engineering teams to build scalable feature stores for optimal model training & execution workflows 
  • Research, evaluate and recommend new tools, applications, software packages for MLOps engineering that can be adopted and approved for use in the CBP environment
  • Collaborate with cross-functional teams (e.g., Software Engineering, Data Science) to integrate and test multiple candidate AI/ML models and applications for operational assessment

Minimum Qualifications:

  • HS Diploma/GED and 20+ years of experience, AS/AA and 18+ years, BS/BA and 12+ years, MS/MA/MBA and 9+ years, or PhD/Doctorate and 7+ years
  • Expertise with MLOps tools and frameworks such as Mlflow, Kubeflow, Airflow and implementing monitoring/drift detection capabilities (e.g. Alibi, Grafana)
  • Experience with ML platforms, such as AWS Sagemaker, DataBricks or DataRobot
  • Experience automating workflow orchestration to handle both batch and real-time streaming data processing for model inference
  • Hands-on experience productionizing models, including experience optimizing for inference speed, containerization (e.g., Docker), and with multi-cloud deployment platforms (e.g., AWS, Azure, Google Cloud Platform)
  • Proficiency in Python, Scala and Java with strong understanding of high-performance computing and GPU acceleration
  • Hands-on experience with Big Data tools (e.g. Spark, Hadoop, Kafka)

Preferred Qualifications:

  • Experience with MLOps principles and tools for automated model training, testing, deployment and monitoring
  • Strong communication skills with the ability to collaborate effectively across Data Science, Data Engineering, and DevSecOps teams
  • Experience with data engineering Extract, Transform and Load (ETL) workflows across various relational/non-relational databases (Oracle/Postgres, MongoDB) and cloud endpoint services e.g. (Lambda,  GraphQL etc.)
  • Experience in using deep learning frameworks (PyTorch, TensorFlow, Keras) and computer vision libraries (OpenCV, SimpleITK, ITKm VTK)
  • Experience with biometric or image recognition algorithms and associated predictive analytics pipelines
  • Experience with GPU-based infrastructure and performance optimization

Clearance Requirements:

Kalyan Ponnam
Technical Recruiter

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20755 Williamsport Pl, Ashburn, VA 20147

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