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Ai Machine Learning Engineer Jobs in Maryland (NOW HIRING)

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... The Logistics AI group is responsible for the intelligence and execution behind Instacart ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... The Logistics AI group is responsible for the intelligence and execution behind Instacart ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... The Logistics AI group is responsible for the intelligence and execution behind Instacart ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... The Logistics AI group is responsible for the intelligence and execution behind Instacart ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... The Logistics AI group is responsible for the intelligence and execution behind Instacart ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... The Logistics AI group is responsible for the intelligence and execution behind Instacart ...

Showing results 21-40

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 Aug 8, 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 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 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 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.

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:
Infographic showing various Ai Machine Learning Engineer job openings in Maryland as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 23% Part Time, 1% Temporary, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $124,976 per year, or $60.1 per hour.

Artificial Intelligence (AI) Engineer

AGE solutions

Fort George G Meade, MD • Hybrid

Full-time

Posted 16 days ago


Job description

About Us
AGE Solutions is a premier technology and professional services company, providing in-depth consulting, advanced technology solutions, and essential services throughout the U.S. government, defense, and intelligence sectors. Prioritizing innovation and client-focused solutions, we assist major agencies in addressing intricate issues and ensuring a more secure future.

AGE Solutions is seeking a highly motivated Artificial Intelligence (AI) Engineer to support our DoD customer's Emerging Technology Mission Assurance initiatives by researching, evaluating, engineering, and integrating Artificial Intelligence (AI), Machine Learning (ML), Generative AI, and other emerging technologies that strengthen Department of Defense cybersecurity and enterprise capabilities.

Working directly with our customer's engineers, industry partners, and government stakeholders, the successful candidate will conduct technology research, support technology assessments and proof-of-concept activities, evaluate commercial and government AI solutions, and provide engineering recommendations that inform enterprise architecture, cybersecurity modernization, and future technology adoption across the DoD Information Network (DoDIN).

Responsibilities Include:

  • Research, evaluate, and assess emerging technologies, including Artificial Intelligence (AI), Machine Learning (ML), Large Language Models (LLMs), Generative AI, cloud computing, cybersecurity, identity management, networking, and advanced computing platforms.
  • Analyze commercial and government technology solutions and provide technical recommendations supporting DISA modernization initiatives.
  • Design, develop, and execute technology evaluations, laboratory testing, pilot programs, and proof-of-concept demonstrations.
  • Develop technology evaluation plans, operational use cases, success criteria, performance metrics, and technical assessment reports.
  • Develop AI prototypes and assist with transitioning successful capabilities into operational environments.
  • Evaluate AI model performance, scalability, security, and operational effectiveness.
  • Apply systems engineering principles throughout technology evaluation, integration, testing, and transition activities.
  • Develop engineering documentation, including architecture diagrams, technical analyses, white papers, CONOPS, and engineering recommendations.
  • Support DISA integration with commercial cloud providers and cloud-hosted AI capabilities.
  • Evaluate AI workloads across hybrid, on-premises, and multi-cloud environments.
  • Collaborate with DISA organizations, DoD agencies, Combatant Commands, industry partners, and other stakeholders to evaluate emerging technologies.
  • Present technical findings, recommendations, and executive briefings to government leadership and Integrated Product Teams (IPTs).
  • Support strategic technology planning, technology roadmaps, business case analyses, and technology migration strategies.

Required Skills, Qualifications, and Experience:

  • Experience:
    • 10 Years of experience
      • 5+ years supporting Artificial Intelligence, Machine Learning, Systems Engineering, Emerging Technologies, Cybersecurity, or Cloud Engineering
  • Education:
    • Bachelor's degree in computer science, Artificial Intelligence, Systems Engineering, Cybersecurity, Information Technology, or a related technical field (or equivalent experience).
  • Security Clearance:
    • Must have and maintain a current DoD Top Secret Clearance.
  • Certifications:
    • Current DoD 8140 baseline certification (e.g., Security+ CE, CEH)
      • Highly Desired: Microsoft Azure AI Engineer Associate or Azure AI Fundamentals AWS Certified AI Practitioner or AWS Machine Learning Engineer
  • Experience with Artificial Intelligence, Machine Learning, Large Language Models (LLMs), Natural Language Processing (NLP), Computer Vision, or Generative AI technologies.
  • Experience conducting technology research, evaluations, proof-of-concepts, or pilot projects.
  • Knowledge of systems engineering principles and technology lifecycle management.
  • Experience with cloud computing platforms and AI-enabled cloud services.
  • Strong analytical, technical writing, and presentation skills.
  • Ability to develop technical documentation, reports, and executive briefings.
  • Strong communication and collaboration skills with government and technical stakeholders.

Preferred Qualifications:

  • Experience supporting DISA, DoD, Federal Government, or Intelligence Community technology modernization programs.
  • Experience with AI governance, Responsible AI, and AI security within government or regulated environments.
  • Experience with commercial cloud platforms such as Microsoft Azure or Amazon Web Services (AWS).
  • Familiarity with Zero Trust Architecture, NIST Risk Management Framework (RMF), and DoD cybersecurity policies.
  • Experience supporting enterprise architecture, technology roadmaps, and modernization initiatives.
  • Experience briefing senior government leadership and executive stakeholders.
  • Experience with DevSecOps, automation, containerization, or Kubernetes.
  • Knowledge of DISA Enterprise Integration and Innovation Center (EIIC), Risk - Management Executive (RME), or emerging technology assessment initiatives.
  • Active Top Secret clearance with SCI eligibility preferred.

Work Environment and Physical Demand:

  • This work will be conducted in an office environment. Must be able to sit for prolonged periods of time.
  • Location and Schedule:
    • Must be within commuting distance of Fort Meade, MD and able to work on-site on a hybrid schedule.
      • 1 day/week onsite required with additional days onsite if the project requires.

The projected salary range for this position is $155,000+ annually. Final compensation will be determined based on factors including years of relevant experience, active security clearance level, certifications, technical skillset, contract requirements, and overall qualifications.

At AGE Solutions, we reward performance, invest in growth, and share success. Our benefits support the whole person, professionally, financially, and personally.

  • 26 Days Paid Leave: Includes vacation, sick, personal time, and holidays. You choose how to use it.
  • Performance Bonuses: Performance bonuses are awarded based on individual contributions and company-wide results, aligning recognition with impact.
  • 401(k) with Match: We match 3% of your contributions with immediate vesting.
  • Financial Protection: Company-paid life insurance up to $300K and options for additional coverage for you and your dependents.
  • Health Benefits: Multiple medical plans, dental, vision, FSA and HSA options to fit your needs.
  • Parental Leave: 15 days of fully paid leave for new parents, because family matters.
  • Military Differential Pay: We bridge the gap for employees on active duty, so they don't take a financial hit while serving.
  • Professional Growth: Paid training and certifications, tuition reimbursement, and the tools and tech to get the job done right.
  • Shared Success: In the event of a company sale, our CEO has committed to returning 80% of net proceeds to employees. This ensures our team shares in the long term value they help create.

At AGE, you'll do work that matters, supported by a company that delivers for its people.