Top 1630 Machine learning engineer Jobs in Springdale Md

Machine Learning Engineer
Lynker Corporation —College Park, MD
- $95,000 - $195,000 a year
- Full-time
- Remote
- English
- Office
- Math
- Paid holidays
- Disability insurance
Senior AI Software Engineer
Que Technology Group —Fort Meade, MD
- Full-time
- Java
- Analysis skills
- Bachelor's degree
- Paid holidays
- Disability insurance
Quick Apply
Okta on Okta Identity Architect
Okta —Washington, DC
- $242,000 - $332,000 a year
- Hybrid work
- Product management
- Fair chance
- Senior level
Quick Apply
Staff TDI Site Reliability Engineer, Okta Federal
Okta —Washington, DC
- $174,000 - $239,000 a year
- Hybrid work
- 7 years
- Software development
- Fair chance
Quick Apply
Cloud Infrastructure Architect, Okta Federal
Okta —Washington, DC
- $244,000 - $336,000 a year
- Hybrid work
- Azure
- DevOps
- Fair chance
Quick Apply
Staff TDI Site Reliability Engineer, Okta Federal
Okta —Washington, DC
- $174,000 - $239,000 a year
- Hybrid work
- 7 years
- Fair chance
- Senior level
Quick Apply
Staff Product Security Engineer, Reviews
Okta —Washington, DC
- $180,000 - $247,500 a year
- Hybrid work
- Windows
- Java
- Mentoring
Quick Apply
Staff Software Engineer - Federal
Okta —Washington, DC
- $161,000 - $221,000 a year
- Hybrid work
- Azure
- AWS
- Fair chance
Quick Apply
Staff AI Security Engineer
Okta —Washington, DC
- $180,000 - $247,500 a year
- Hybrid work
- Computer science
- Computer Science
- 8 years
Quick Apply
Senior Manager, Site Reliability Engineering (Federal)
Okta —Washington, DC
- $207,000 - $284,900 a year
- Hybrid work
- 5 years
- AWS
- Presentation skills
Quick Apply
Government and Public Sector - AI & Data - GenAI Developer - Manager
EY —McLean, VA
- $125,500 - $261,600 a year
- Computer science
- Azure
- Computer Science
- Paid holidays
- Health insurance
4d
VDI Engineer
General Dynamics Information Technology —Springfield, VA
- $115,600 - $156,400 a year
- 7 years
- DevOps
- Windows
- Paid time off
- 401(k) matching
Data Architect
WSSC Water —Laurel, MD
- $135,814 - $231,251 a year
- Full-time
- System design
- HIPAA
- Office
Signal and Image Processing Engineer
Johns Hopkins Applied Physics Laboratory (APL) —Laurel, MD
- $85,000 - $195,000 a year
- Full-time
- Computer science
- Computer Science
- Bachelor of Science
- Disability insurance
- Health insurance
Software/Agentic Engineer (Early Career)
Rockridge Construction —Vienna, VA
- $90,000 - $110,000 a year
- Full-time
- Hybrid work
- Google Workspace
- 1 year
- Entry level
Quick Apply
Senior Electronic and Optical Materials Device Fabrication Engineer
Johns Hopkins Applied Physics Laboratory (APL) —Laurel, MD
- $105,000 - $290,000 a year
- Full-time
- 7 years
- Master's degree
- Databases
- Disability insurance
- Health insurance
Naval Marine Engineer
CACI —Washington, DC
- $86,600 - $181,800 a year
- Full-time
- Hybrid work
- Microsoft Excel
- OSHA
- 5 years
- Health insurance
Senior Principal Software Engineer
General Dynamics Mission Systems, Inc —Annapolis Junction, MD
- $183,381 - $193,049 a year
- Full-time
- Hybrid work
- System design
- Master's degree
- 8 years
- Paid parental leave
- Health insurance
Strategic Artificial Intelligence (AI) Engineer
Computer World Services —Fort Meade, MD
- $130,000 - $150,000 a year
- Hybrid work
- Computer science
- Computer Science
- Engineering
Senior System Engineer for Special Operations
Johns Hopkins Applied Physics Laboratory (APL) —Laurel, MD
- $105,000 - $290,000 a year
- Full-time
- 5 years
- Engineering
- Analysis skills
- Disability insurance
- Health insurance

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Machine Learning Engineer

Lynker Corporation -
College Park, MD

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Job Details

Full-time
$95,000 - $195,000 a year

Benefits

Paid holidays
Disability insurance
Health insurance
Dental insurance
401(k)
Flexible spending account
Tuition reimbursement
Paid time off
Employee assistance program
Vision insurance
401(k) matching
Employee stock ownership plan
Referral program

Qualifications

AI models
Radar data analysis
GPU programming
TensorFlow
Data quality checks
Systems integration
Software engineering
Data Integration (Data management)
Engineering development testing
Requirements design
PyTorch
High-performance computing clusters
Data quality assurance
Software implementation
UNIX
English
Meteorological data collection
AI platforms (beyond public GPTs)
Computational framework
Computational modeling
Development environments
System design for system development
Data quality management
Machine intelligence
Math
Data pipeline scheduling
Environmental data analysis
Model deployment
System validation
System testing

Full 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.

Apply Now

Refine Your Search

machine learning engineer jobs in springdale md

Machine Learning Engineer

Senior AI Software Engineer

Okta on Okta Identity Architect

Staff TDI Site Reliability Engineer, Okta Federal

Cloud Infrastructure Architect, Okta Federal

Staff TDI Site Reliability Engineer, Okta Federal

Staff Product Security Engineer, Reviews

Staff Software Engineer - Federal

Staff AI Security Engineer

Senior Manager, Site Reliability Engineering (Federal)

Government and Public Sector - AI & Data - GenAI Developer - Manager

VDI Engineer

Data Architect

Signal and Image Processing Engineer

Software/Agentic Engineer (Early Career)

Senior Electronic and Optical Materials Device Fabrication Engineer

Naval Marine Engineer

Senior Principal Software Engineer

Strategic Artificial Intelligence (AI) Engineer

Senior System Engineer for Special Operations

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