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Senior Machine Learning Ops Engineer Jobs in Virginia

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 ...

Senior Machine Learning Engineer

Mclean, VA · On-site

$105K - $145K/yr

We are where innovation meets purpose; and where your career can meet purpose as well.  We are looking for a Senior Machine Learning Engineer to that will focus on researching, designing, training ...

Senior Machine Learning Engineer

Mclean, VA · On-site

$105K - $145K/yr

We are looking for a Senior Machine Learning Engineer to that will focus on researching, designing, training, and evaluating machine learning models to solve complex, real-world problems. We ...

Senior Machine Learning Engineer

Mclean, VA · On-site

$105K - $145K/yr

We are looking for a Senior Machine Learning Engineer to that will focus on researching, designing, training, and evaluating machine learning models to solve complex, real-world problems. We ...

Senior Machine Learning Engineer

Mclean, VA

$105K - $145K/yr

Senior Machine Learning Engineer Location: McLean, VA (hybrid); occasional travel to Durham, NC and customer sites About CoVar CoVar is a small AI/ML R&D software company with offices in Durham, NC ...

Sr. Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part ... The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this ...

Sr. Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

Sr. Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE) , you'll be ... The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this ...

Sr Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part ... The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this ...

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Senior Machine Learning Ops Engineer information

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.
What are the most commonly searched types of Machine Learning Ops Engineer jobs in Virginia? The most popular types of Machine Learning Ops Engineer jobs in Virginia are:
What job categories do people searching Senior Machine Learning Ops Engineer jobs in Virginia look for? The top searched job categories for Senior Machine Learning Ops Engineer jobs in Virginia are:
What cities in Virginia are hiring for Senior Machine Learning Ops Engineer jobs? Cities in Virginia with the most Senior Machine Learning Ops Engineer job openings:

Sr. Machine Learning Engineer

Hirekeyz Inc

Fort Belvoir, VA • On-site

$118K - $162K/yr

Contractor

Posted 26 days ago


Job description

Role: Sr. Machine Learning Engineer

Location: Ft. Belvoir, VA (On-site with Hybrid Option)

Duration: Long Term Contract

Clearance: DOD Top Secret Clearance (Must)

Job Description:

As a consultant, will be working to assist a DoD U.S. Army Command to create cybersecurity solutions working with cloud-based architecture (AWS Services).  You will work directly the stakeholders to understand requirements and work with Army’s Security teams to ensure the technologies available to the Government can be turned into solutions that they can use. Liaise with government software vendors and other asset creators; lead coordination of point solutions into broader capabilities for Army Defense Cyber Operations (DCO).  You will be helping our military defend our cyber security infrastructure by delivering software capabilities. 

Required Skills:

  • Bachelor's degree in Computer Science, Mathematics, Statistics, or a related field
  • Master’s Degree in Data Science, Machine Learning, or a related field
  • Proven experience in a machine learning or AI engineering role
  • Strong proficiency in Python, C++, or Java
  • Extensive experience with machine learning frameworks such as TensorFlow, PyTorch, or Keras
  • Familiarity with cloud platforms (AWS, Google Cloud, Azure) for deploying ML solutions
  • Experience with data preprocessing, feature engineering, and model selection
  • Knowledge of data structures, algorithms, and software architecture
  • Excellent problem-solving abilities and attention to detail
  • Strong communication skills, with the ability to present complex technical concepts to non-technical stakeholders
  • Commitment to writing clean, efficient, and well-tested code
  • Self-motivated, with the ability to work effectively both independently and in a team environment

Preferred Skills:

  • Certifications in Machine Learning / Artificial Intelligence / Data Science
  • Familiarity with agile development methodologies
  • 3-5 years of experience in a ML/AI development role