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Machine Learning Engineer Jobs in Gaithersburg, MD

AISquared

Machine Learning Engineer

Washington, DC · On-site

Job Summary : aisquared is a company focused on AI solutions, and they are seeking a highly skilled Machine Learning Engineer to join their core AI team. In this role, you will be responsible for ...

10a Labs

Machine Learning Engineer

Washington, DC · On-site +1

$130K - $200K/yr

We are seeking a Machine Learning Engineer (3-5+ years of experience) to help design, build, evaluate, and deploy advanced machine learning systems across a range of safety, security, and ...

Spear AI

Machine Learning Engineer

Washington, DC · On-site +1

We're seeking a skilled Machine Learning Engineer to build and deploy production ML systems for the next-generation data management and artificial intelligence platform for maritime domain awareness.

10a Labs

Machine Learning Engineer

Washington, DC · On-site

$130K - $200K/yr

We are seeking a Machine Learning Engineer (3-5+ years of experience) to help design, build, evaluate, and deploy advanced machine learning systems across a range of safety, security, and ...

Somatus, Inc.

Machine Learning Engineer

Mclean, VA · On-site

$105K - $115K/yr

As a Machine Learning Engineer at Somatus, you will work collaboratively with our data and technology teams to help clinical, operational, and financial partners solve advanced analytical problems.

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

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. You ...

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

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. You ...

Kitware

Machine Learning Engineer

Arlington, VA · On-site

$110K - $160K/yr

... machine learning, artificial intelligence, and computer vision * Perform rapid prototyping and enhanced development to be integrated into operational systems * Contribute your strong programming ...

Capital One

Lead Machine Learning Engineer

Mclean, VA · On-site +1

$103K - $136K/yr

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. You ...

Kitware

Machine Learning Engineer

Arlington, VA · Hybrid

$110K - $160K/yr

... machine learning, artificial intelligence, and computer vision * Perform rapid prototyping and enhanced development to be integrated into operational systems * Contribute your strong programming ...

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All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Gaithersburg, MD

Machine Learning Engineer information

See Gaithersburg, MD salary details

$34K

$139.1K

$209.1K

How much do machine learning engineer jobs pay per year?

As of Jul 13, 2026, the average yearly pay for machine learning engineer in Gaithersburg, MD is $139,129.00, according to ZipRecruiter salary data. Most workers in this role earn between $109,700.00 and $167,500.00 per year, depending on experience, location, and employer.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-demand industries or companies can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially in tech giants or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as AI advances, as they develop and refine algorithms, models, and systems. Roles that require complex problem-solving, creativity, and domain expertise—such as healthcare professionals, data scientists, software developers, cybersecurity specialists, and AI ethics officers—are also expected to persist due to their reliance on human judgment and specialized knowledge. These jobs often involve skills that are difficult for AI to fully replicate or replace.

What Does a Machine Learning Engineer Do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What engineers make $300,000 a year?

Senior machine learning engineers and data scientists with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $300,000 or more annually, especially in high-cost-of-living areas or top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on business outcomes.

What are some common challenges faced by Machine Learning Engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

More about Machine Learning Engineer jobs
What are the most commonly searched types of Machine Learning Engineer jobs in Gaithersburg, MD? The most popular types of Machine Learning Engineer jobs in Gaithersburg, MD are:
What are popular job titles related to Machine Learning Engineer jobs in Gaithersburg, MD? For Machine Learning Engineer jobs in Gaithersburg, MD, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Gaithersburg, MD look for? The top searched job categories for Machine Learning Engineer jobs in Gaithersburg, MD are:
What cities near Gaithersburg, MD are hiring for Machine Learning Engineer jobs? Cities near Gaithersburg, MD with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Gaithersburg, MD as of July 2026, with employment types broken down into 90% Full Time, 7% Part Time, and 3% Contract. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution, with an average salary of $139,129 per year, or $66.9 per hour.

Machine Learning Engineer

AISquared

Washington, DC • On-site

Full-time

Re-posted 22 days ago

Job description

Job Summary:
aisquared is a company focused on AI solutions, and they are seeking a highly skilled Machine Learning Engineer to join their core AI team. In this role, you will be responsible for deploying, maintaining, and monitoring AI/ML systems, while collaborating with data scientists and product teams to ensure reliable and efficient solutions.
Responsibilities:
• Design, implement, and maintain ML deployment pipelines for scalable production systems.
• Operationalize large language models (LLMs) and other AI/ML models, ensuring high availability and reliability.
• Build robust model monitoring, logging, and alerting systems to track performance and detect drift.
• Partner with data scientists to transition models from research/prototype into production-ready deployments.
• Develop CI/CD pipelines for ML workflows, integrating testing, validation, and automated deployment.
• Optimize runtime performance of ML models across cloud platforms (AWS, GCP, Azure) and distributed systems.
• Apply containerization and orchestration (Docker, Kubernetes) to enable reproducible, scalable systems.
• Collaborate with cross-functional teams to ensure ML systems align with platform goals and business requirements.
Qualifications:
Required:
• 5+ years of experience as a Machine Learning Engineer, MLOps Engineer, or similar role.
• Proven experience deploying and maintaining machine learning models in production at scale.
• Hands-on experience with ML lifecycle tooling (MLflow, Kubeflow, SageMaker, Vertex AI, or similar).
• Strong proficiency in Python; familiarity with ML frameworks such as PyTorch or TensorFlow.
• Deep knowledge of containerization (Docker) and orchestration (Kubernetes) for production ML systems.
• Expertise with cloud platforms (AWS, GCP, Azure) for ML deployment and scaling.
• Strong understanding of MLOps best practices, monitoring, and automation.
• Excellent problem-solving skills, with an emphasis on building reliable, scalable systems.
• Strong communication and collaboration skills across technical and non-technical teams.
Company:
AISquared is a SaaS that provides AI model integration, real-time insights, data analytics, and optimization services. Founded in 2021, the company is headquartered in Mountain View, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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