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Ai Machine Learning Engineer Jobs in Maryland (NOW HIRING)

Columbia Technology Partners

$150 - $230/hr

Description Columbia Technology Partners is seeking an AI/ML Engineer to support mission‑critical ... Experience with machine learning frameworks including PyTorch, TensorFlow, vLLM, or llama.cpp.

BOOZ, ALLEN & HAMILTON, INC.

$77K - $176K/yr

As an experience d AI and ML engineer, you know that machine learning is critical to understanding and processing massive datasets. Your ability to conduct statistical analyses on business processes ...

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All JobsAi Machine Learning Engineer JobsAi Machine Learning Engineer Jobs in Maryland

Ai Machine Learning Engineer information

See Maryland salary details

$30.6K

$125K

$187.8K

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

As of Sep 6, 2026, the average yearly pay for ai machine learning engineer in Maryland is $124,976.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $150,400.00 per year, depending on experience, location, and employer.

What is an AI machine learning engineer?

An AI Machine Learning Engineer is a professional who designs, builds, and deploys artificial intelligence and machine learning models to solve real-world problems. They work with large datasets, select appropriate algorithms, and optimize models for accuracy and efficiency. Their role often involves both software engineering and data science skills, and they collaborate with other teams to integrate these models into products or services. AI Machine Learning Engineers are in high demand across industries such as technology, healthcare, finance, and more.

What are the key skills and qualifications needed to thrive as an AI machine learning engineer?

To thrive as an AI Machine Learning Engineer, you need a strong background in mathematics, statistics, programming (often Python or R), and a relevant degree such as computer science or engineering. Familiarity with frameworks like TensorFlow, PyTorch, and scikit-learn, as well as experience with cloud platforms and data processing tools, is highly valued, along with certifications in AI or machine learning. Critical thinking, problem-solving, and effective communication are essential soft skills for collaborating with teams and translating business needs into technical solutions. These competencies are crucial for developing accurate, scalable AI models that deliver real-world value and drive innovation.

What are some common challenges that AI machine learning engineers face when deploying models to production environments?

AI Machine Learning Engineers often encounter challenges such as ensuring model scalability, managing data pipeline reliability, and handling model drift once solutions are live. They also need to collaborate closely with DevOps and software engineering teams to integrate models seamlessly into existing systems, while maintaining performance and security. Addressing these challenges requires a strong understanding of both machine learning principles and software deployment best practices.

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

AspectAi Machine Learning EngineerData Scientist
CredentialsDegree in CS, AI, or related fields; certifications in ML frameworksDegree in CS, Statistics, or related fields; certifications in data analysis
Work EnvironmentDevelops and deploys ML models in production systemsAnalyzes data, builds models, and provides insights
Industry UsageTech, finance, healthcare, where deploying ML models is keyResearch, business intelligence, analytics across industries

While both roles involve working with data and machine learning, Ai Machine Learning Engineers focus on building and deploying scalable ML models in production environments, whereas Data Scientists primarily analyze data and develop models for insights. The roles often overlap but differ in their core focus and responsibilities.

Is AI Machine Learning Engineer in demand?

AI Machine Learning Engineers are in high demand due to the growing adoption of artificial intelligence across industries. They typically require skills in programming, data analysis, and familiarity with tools like TensorFlow or PyTorch, and job opportunities are expected to continue expanding as AI applications become more widespread.

What are popular job titles related to Ai Machine Learning Engineer jobs in Maryland?

For Ai Machine Learning Engineer jobs in Maryland, the most frequently searched job titles are:

What job categories do people searching Ai Machine Learning Engineer jobs in Maryland look for?

The top searched job categories for Ai Machine Learning Engineer jobs in Maryland are:

Ai Machine Learning Engineer jobs near you
Infographic showing various Ai Machine Learning Engineer job openings in Maryland as of August 2026, with employment types broken down into 1% As Needed, 79% Full Time, 19% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $124,976 per year, or $60.1 per hour.

AI/Machine Learning Engineer

Optimus Technology, Inc.

Fort George G Meade, MD • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 14 days ago

Job description

Intelligence Analysts rely on multi-step workflows that are time sensitive, detail rich, and critical to national security. As an AI/Machine Learning Engineer, you will work directly with mission users to capture these workflows, document operational decision points, and translate them into effective AI enabled capabilities.
You will design and implement solutions that may include LLM powered workflows, agent based automation, or hybrid approaches depending on mission needs. Your work will streamline analytical tasks, improve data accessibility, and support rapid, informed decision making in high tempo enviornments.
You'll collaborate with operators, analysts, developers, and mission leadership to ensure solutions integrate cleanly with existing systems, perform reliably in production, and adhere to security and governance expectations of classified enviornments.
Required Skills:
-Experience capturing user workflows and translating them into structured process maps, automation requirements, or executable logic.
-Experience designing or implementing LLM based on agentic workflows, including multi-step reasoning, tool integrations, and orchestration.
-Experience integrating AI systems with APIs, enterprise data stores, or mission platforms.
-Experience with programming languages such as Python.
Desired Skills:
-Experience engineering AI capabilities on premise or multi classification enviornments.
-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 mission oriented analytical processes.
Optimus Technology is a SDVO (Service-Disabled Veteran-Owned) small business founded in 2010. We are known for our exceptionally talented group of Engineers and Technical experts with superior knowledge and experience in Cyber Technologies and the latest technology trends. Our dedication in pairing the right Optimus Technologist with the right customer solution is at the core of our Partnership commitment and critical to the performance and satisfaction of our employees, the pinnacle of the Optimus culture.
Why us?
We strive to provide the best well-rounded benefits package available.
  • Premium health, dental, and vision package
  • Company funded HRA
  • 401k company contributions
  • Employer paid group term life insurance policy
  • Tuition assistance and career development
  • Short-term and long-term disability
  • Paid time off
  • Referral bonuses
  • Company outings, giveaways & more

Optimus practices a policy of non-discrimination and is fully committed to the principles of equality in employment and opportunity for all employees. Employment decisions are made without regard to age, gender, race, religion, marital status, national origin, sexual orientation, or any other non-merit based factor.

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