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Senior Machine Learning Engineer Jobs in Vienna, VA

Capital One

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 part of an Agile team dedicated to productionizing machine learning applications and systems at scale.

Autodesk

Senior Machine Learning Test Engineer

Washington, DC · On-site +1

$125K - $162K/yr

Job Requisition ID # 26WD98377 Senior Machine Learning Test Engineer Location: United States East Coast Position Overview As a Senior Machine Learning Test Engineer in the Research Enablement team ...

AI Squared

Machine Learning Engineer

Washington, DC · On-site

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled Machine Learning Engineer to join our core AI team. In this role, you will focus on deploying ...

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All JobsMachine Learning Engineer JobsSenior Machine Learning Engineer JobsSenior Machine Learning Engineer Jobs in Vienna, VA

Senior Machine Learning Engineer information

See Vienna, VA salary details

$59.7K

$127K

$184.2K

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

As of Aug 9, 2026, the average yearly pay for senior machine learning engineer in Vienna, VA is $127,025.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,900.00 and $144,000.00 per year, depending on experience, location, and employer.

What are some common challenges senior machine learning engineers face when deploying models to production, and how can they be addressed?

Senior Machine Learning Engineers often encounter challenges related to model scalability, maintaining performance in real-world scenarios, and ensuring reliable integration with existing systems. Addressing these challenges typically involves thorough testing, implementing robust monitoring for model drift, and collaborating closely with DevOps and software engineering teams to streamline deployment pipelines. Staying updated on best practices in MLOps and adopting tools for automated deployment and monitoring can greatly improve the reliability and efficiency of production models.

What does a senior machine learning engineer do?

A Senior Machine Learning Engineer designs, develops, and implements machine learning models to solve complex problems. They are responsible for selecting appropriate algorithms, preprocessing data, and optimizing model performance. Additionally, they collaborate with data scientists, software engineers, and product teams to integrate machine learning solutions into production systems. Senior engineers also mentor junior team members and contribute to setting technical direction for machine learning projects.

What are the key skills and qualifications needed to thrive as a senior machine learning engineer, and why are they important?

To thrive as a Senior Machine Learning Engineer, you need advanced knowledge of machine learning algorithms, statistical modeling, and programming languages like Python or Java, typically supported by a degree in computer science or a related field. Experience with frameworks and tools such as TensorFlow, PyTorch, scikit-learn, and cloud platforms, as well as familiarity with version control and CI/CD systems, is essential. Strong problem-solving, communication, and leadership skills help you collaborate effectively and mentor junior team members. These capabilities are crucial for designing scalable ML solutions and driving impactful results within complex, dynamic projects.

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

AspectSenior Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience with ML frameworksBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops and deploys ML models in production systemsAnalyzes data, builds models, and provides insights
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, tech

While both roles require strong technical skills and knowledge of machine learning, Senior Machine Learning Engineers focus more on deploying scalable ML solutions in production environments, whereas Data Scientists primarily analyze data and develop models for insights. The roles often overlap but differ in their core responsibilities and focus areas.

What cities near Vienna, VA are hiring for Senior Machine Learning Engineer jobs? Cities near Vienna, VA with the most Senior Machine Learning Engineer job openings:
Senior Machine Learning Engineer jobs near you
Infographic showing various Senior Machine Learning Engineer job openings in Vienna, VA as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $127,025 per year, or $61.1 per hour.

ML Engineer

Indotronix International Corporation

Mclean, VA • On-site

Contractor

This job post has expired today. Applications are no longer accepted.

Job description

ML Engineer | McLean, Virginia, United States Senior Machine Learning Engineer - McLean, VA (Hybrid, 12+ Month Contract) About the Role Join a high-impact Machine Learning Engineering team at a leading financial services organization, driving production ML systems for critical platforms such as credit decisioning, fraud detection, and risk assessment. As a Senior Machine Learning Engineer, you will partner with cross-functional teams to develop, scale, and optimize cloud-native ML solutions. This is an opportunity to shape enterprise-scale AI platforms, influence engineering standards, and work with the latest cloud and MLOps technologies. Responsibilities - Design, develop, and deploy production-grade machine learning solutions on AWS - Build and maintain scalable ML pipelines for model training, validation, deployment, and monitoring - Collaborate with Data Scientists to operationalize advanced ML models - Develop and optimize cloud-native infrastructure to support enterprise ML workloads - Implement best practices across the ML lifecycle, including testing, CI/CD, governance, and monitoring - Support and enhance platforms powering credit decisioning, fraud detection, risk assessment, and partner programs - Contribute to the evolution of ML platform capabilities and engineering standards Required Skills and Experience - 5+ years in Machine Learning Engineering, Software Engineering, or related fields - Proficiency in Python (Spark, Pandas, NumPy) - Deep expertise in AWS (ECS, EC2, EKS, S3), cloud-native architectures - Strong understanding of MLOps principles and production ML deployment - Experience with distributed data processing (Apache Spark) - Solid software engineering fundamentals: version control, testing, CI/CD practices - Hybrid on-site work in McLean, VA (Tuesday-Thursday) Preferred Skills - Experience with Databricks and modern analytics platforms - Strong SQL and data analysis background - End-to-end ML platform development - Familiarity with feature stores, model monitoring, and ML observability - AWS Solutions Architect or similar certifications - Hands-on with Kubernetes, Kubeflow, workflow orchestration tools - Exposure to Generative AI, LLM deployment, or AI platform engineering Benefits - Work on mission-critical AI platforms at enterprise scale - Collaborative, cross-functional team environment - Opportunity to drive innovation in financial services ML applications - Professional growth with exposure to the latest cloud, MLOps, and AI technologies - Competitive compensation on a long-term contract How to Apply If you're passionate about building and scaling production ML systems, and want to make an impact in financial services, apply now with your updated resume.
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About Indotronix

Sourced by ZipRecruiter

In 1986, Indotronix established itself in the staffing space. 22 years later, Avani entered the scene, offering consulting and technology development. Finally, in 2016, the two joined forces to begin delivering talent across all areas, from Staffing to Consulting to unique platform development.

Industry

Recruiting and staffing services

Company size

1,001 - 5,000 Employees

Headquarters location

Rochester, NY, US

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