Machine Learning Engineer

🕒 July 15

🦀 Maryland – Remote

🦀 Maryland – Remote

💵 $95k - $195k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Machine Learning Engineer

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Lynker

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2007

💼 Consulting

🔬 Science

Consulting • Science • Engineering

Lynker is a premier science, engineering, and technology company that specializes in providing innovative solutions in weather and climate science, marine/ocean science and engineering, and space weather and space climate. The company partners with governments, communities, and industries to deliver impactful services that address global environmental security and economic prosperity. By leveraging a team of skilled scientists, engineers, and educators, Lynker tackles some of the nation’s most important missions and challenges, while also focusing on training, communications, and outreach for effective environmental policy and compliance.

📋 Description

• 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. • 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.

🎯 Requirements

• 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. • 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.

🏖️ Benefits

• 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