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Machine Learning Engineer Jobs in Pasadena, MD (NOW HIRING)

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Machine Learning Engineer information

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$32K

$130.7K

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How much do machine learning engineer jobs pay per year?

As of Aug 23, 2026, the average yearly pay for machine learning engineer in Pasadena, MD is $130,719.00, according to ZipRecruiter salary data. Most workers in this role earn between $103,000.00 and $157,300.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

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 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 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.

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.

What are the most commonly searched types of Machine Learning Engineer jobs in Pasadena, MD?

The most popular types of Machine Learning Engineer jobs in Pasadena, MD are:

What are popular job titles related to Machine Learning Engineer jobs in Pasadena, MD?

For Machine Learning Engineer jobs in Pasadena, MD, the most frequently searched job titles are:

What cities near Pasadena, MD are hiring for Machine Learning Engineer jobs?

Cities near Pasadena, MD with the most Machine Learning Engineer job openings:

Infographic showing various Machine Learning Engineer job openings in Pasadena, MD as of August 2026, with employment types broken down into 43% Full Time, 43% Part Time, and 14% Contract. Highlights an 86% In-person, and 14% Remote job distribution, with an average salary of $130,719 per year, or $62.8 per hour.

Artificial Intelligence/Machine Learning Engineer

Everwatch

Annapolis Junction, MD โ€ข On-site

$47.60 - $108.18/hr

Full-time

Re-posted 11 days ago


Job description

EverWatch is a government solutions company providing advanced defense, intelligence, and deployed support to our countryโ€™s most critical missions.  We are a full-service government solutions company. Harnessing the most advanced technology and solutions, we strengthen defenses and control environments to preserve continuity and ensure mission success.

EverWatch employees are focused on tackling the most difficult challenges of the US Government. We offer the best salaries and benefits packages in our industry - to identify and retain the top talent in support of our critical mission objectives.

Commitment to Non-Discrimination:

All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state, local, or international law.


Cyber and intelligence analysts rely on multistep workflows that are timesensitive, detailrich, and critical to national security. As an Artificial Intelligence/Machine Learning Engineer, you will work directly with mission users to capture these workflows, document operational decision points, and translate them into effective AIenabled capabilities.

You will design and implement solutions that may include LLMpowered workflows, agentbased automation, or hybrid approaches depending on mission needs. Your work will streamline analytical tasks, improve data accessibility, and support rapid, informed decisionmaking in hightempo environments.

Youโ€™ll collaborate with operators, analysts, developers, and mission leadership to ensure solutions integrate cleanly with existing systems, perform reliably in production, and adhere to the security and governance expectations of classified environments.

Join us. The world canโ€™t wait.


You Have: 

  • Experience capturing user workflows and translating them into structured process maps, automation requirements, or executable logic
  • Experience designing or implementing LLMbased or agentic workflows, including multistep reasoning, tool integrations, and orchestration
  • Experience integrating AI systems with APIs, enterprise data stores, or mission platforms
  • Experience with programming languages such as Python
  • TS/SCI clearance with a polygraph 
  • Bachelorโ€™s degree and 3+ years of experience in AI/ML engineering, data science, or software engineering within cyber, intelligence, or national security environments, 6+ years of experience in AI/ML engineering, data science, or software engineering within cyber, intelligence, or national security environments in lieu of a degree, OR Master's degree and technical experience

Nice If You Have: 

  • Experience engineering AI capabilities in onpremise or multiclassification environments
  • Experience with AWS or Azure, including work in restricted or classified environments
  • Experience with AI/LLM development framework such as LangChain, LangGraph, PydanticAI, or CrewAI
  • Experience with ML frameworks such as PyTorch, TensorFlow, vLLM, or llama.cpp
  • Experience with cyber or intelligence workflows, operational data types, or missionoriented analytical processes
  • Masterโ€™s degree in AI, ML, Data Science, Cybersecurity, or Engineering

Clearance:

Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information; TS/SCI clearance with a polygraph is required. 

Compensation at EverWatch is determined by various factors, including but not limited to location, the individualโ€™s particular combination of education, knowledge, skills, competencies, and experience, as well as contract-specific affordability and organizational requirements. The projected compensation range for this position is $47.60 to $108.18 per hour.  The estimate displayed represents the typical compensation range for this position and is just one component of EverWatchโ€™s total compensation package for employees.


US-MD-Annapolis Junction
AI/ML, LLM, API, Python