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Senior Machine Learning Engineer Jobs in Annapolis, 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 ...

Beyond SOF

Engineer, Machine Learning

Washington, DC · On-site

The Machine Learning Engineer is responsible for developing and implementing machine learning models and algorithms to solve complex problems. Main Responsibilities and Duties: Develop and implement ...

SwiftCruit

Machine Learning Engineer

Washington, DC · On-site

$100 - $150/hr

For this position, we are seeking a talented individual to join AIS as a Senior Software Engineer ... Project Summary AIS is seeking a Machine Learning Engineer for an AI Engineering contract ...

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 ...

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All JobsMachine Learning Engineer JobsSenior Machine Learning Engineer JobsSenior Machine Learning Engineer Jobs in Annapolis, MD

Senior Machine Learning Engineer information

See Annapolis, MD salary details

$58.9K

$125.3K

$181.7K

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

As of Aug 11, 2026, the average yearly pay for senior machine learning engineer in Annapolis, MD is $125,282.00, according to ZipRecruiter salary data. Most workers in this role earn between $103,400.00 and $142,100.00 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 are popular job titles related to Senior Machine Learning Engineer jobs in Annapolis, MD? For Senior Machine Learning Engineer jobs in Annapolis, MD, the most frequently searched job titles are:
What cities near Annapolis, MD are hiring for Senior Machine Learning Engineer jobs? Cities near Annapolis, MD 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 Annapolis, MD as of August 2026, with employment types broken down into 1% As Needed, 71% Full Time, 25% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $125,282 per year, or $60.2 per hour.

Machine Learning Engineer

Lynker Corporation

College Park, MD • On-site, Remote

$95K - $195K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 27 days ago

Job description

Overview
Lynker is seeking a talented and experienced Machine Learning Engineer to support the Environmental Modeling Center (EMC) within the National Centers for Environmental Prediction (NCEP). The primary objective of this role is to assist in the development of ML based systems that predict the current weather conditions everywhere given sparse observation data (this process is known as Data Assimilation [DA]). . These systems will complement existing physics-based systems and be tested as independent prototypes, running alongside traditional DA workflows. The position is located at the NOAA Center for Weather and Climate Prediction (NCWCP) in College Park, MD.
Responsibilities
Duties of the Machine Learning Engineer will include the following:
The Machine Learning Engineer will perform their job duties to a high standard, working both independently and collaboratively.The core responsibility is to assist in the development, implementation, testing, and evaluation of an AI-based Real-Time Mesoscale Analysis (AI-RTMA) system in support of NOAA's National Blend of Models (NBM). The AI-RTMA system will generate high spatial and temporal resolution analyses of meteorological variables to reduce biases in the NBM fields.. Because these fields serve as the foundation for gridded forecasts issued by the National Weather Service, this system will directly contribute to improved forecast quality.
The successful Machine Learning Engineer will work on the following scientific and engineering tasks:
  • Conduct a comprehensive review of state-of-the-art AI-based data assimilation and end-to-end weather forecasting methodologies, systems, and frameworks. Communicate findings with EMC scientists and external partners to inform the development of a scientifically robust and efficient AI-RTMA approach.
  • Collaborate with NOAA's NBM team and key stakeholders to define product requirements for AI-RTMA, including domain configuration, grid structure, output variables, spatial and temporal resolution, and data formats suitable for operational evaluation and transition.
  • Design, implement, and maintain robust data pipelines to support AI-RTMA training, validation, testing, and evaluation. This includes collecting, formatting, quality-controlling, and integrating diverse observational datasets (e.g., conventional observations, satellite, radar, and other sources), as well as preparing model inputs, targets, metadata, and training/validation splits.
  • Develop, train, rigorously test, and deploy a fully functional AI-RTMA system based on selected AI frameworks or architectures.
  • Implement cross-validation and other evaluation methodologies to quantify model performance and reliability during inference.

Qualifications
The Machine Learning Engineer selected should have the following:
  • Experience developing, training and deploying AI-based systems applied to geophysical systems.
  • Experience with common AI frameworks such as PyTorch, TensorFlow.
  • Experience working with earth observation data, including conventional observations, satellite, radar.
  • Excellent Python programming skills.
  • Practical experience utilizing High Performance Computers (HPCs) and GPUs.
  • Proven experience working in a UNIX environment with advanced scripting languages.
  • Good communication skills, both oral and written, in English.

The Ideal Machine Learning Engineer will have the following:
  • In-depth knowledge of data assimilation techniques (observation forward modeling, quality control, variational-based and/or ensemble methods).
  • Strong foundation in the physical, statistical and mathematical basis of geophysical modeling (atmospheric and/or environmental).
  • Experience with cloud platforms and use of IDEs for development.
  • Experience with cloud-native data formats such as Zarr, Parquet.
  • Experience with compiled languages.
  • Comfort using agentic AI tools to accelerate development.
  • Experience executing numerical models on HPC platforms using parallelization frameworks and job scheduling systems.
  • Familiarity with coupled earth system models.
  • Knowledge of modern software engineering practices (requirements gathering, design, prototyping, version control, integration, testing, and documentation).
  • Prior experience in model testing, evaluation, or knowledge of verification principles.

About Lynker
Lynker is a growing, employee owned business, specializing in professional, scientific and technical services. Our continually expanding team combines scientific expertise with mature, results-driven processes and tools to achieve technically sound, cost effective solutions in hydrology/water sciences, geospatial analysis, information technology, resource management, conservation, and management and business process improvement.
We focus on putting the right people in the right place to be effective. And having the right people is critical for success. Our streamlined organization enables and empowers our talented professionals to tackle our customers' scientific and technical priorities - creatively and effectively.
Lynker offers a team-oriented work environment, and the opportunity to work in a culture of exceptionally skilled professionals who embrace sound science and creative solutions. Lynker's benefits include the following:
  • Comprehensive healthcare for the employee at no monthly cost
  • Healthcare benefit covers medical, prescription drug, dental, and vision
  • Personal Time Off (PTO) Policy plus paid holidays
  • Highly competitive compensation plan regularly calibrated against industry and location benchmarks
  • 401(k) retirement plan with company-matching
  • Employee Stock Ownership Plan (ESOP) - we're all company owners!
  • Flexible spending accounts
  • Employee assistance program (EAP)
  • Short- and long-term disability insurance
  • Life and accident insurance
  • Tuition assistance/Training/Workforce improvement reimbursement per year
  • Spot bonuses for exceptional performance
  • Annual Employee Recognition Awards with bonuses
  • Employee Referral Program
  • Free centralized, self-directed Learning Management System to learn at your own pace
  • Personalized career growth plans for every employee

Lynker is an E-Verify employer.
Lynker is an equal opportunity employer and makes all employment decisions based on merit, qualifications, and business needs. We do not discriminate on the basis of race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, marital status, veteran status, or any other legally protected status under federal, state, or local laws.
⚠ Fraud Alert: Recruitment Scam Warning: Lynker has been made aware of fraudulent individuals posing as Lynker recruiters and offering fake job opportunities. All legitimate Lynker job postings are listed on our official careers page. Communication from Lynker recruiters will come from an official @lynker.com email address.

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