Machine Learning Engineer

Machine Learning EngineerMachine Learning EngineerFull TimeRemoteSeniorTeam 501-1,000Since 2007H1B SponsorCompany SiteLinkedIn

Location

Maryland

Posted

5 days ago

Salary

$95K - $195K / year

Seniority

Senior

Bachelor DegreeEnglishCloudPythonPyTorchTensorflowUnix

Job Description

Machine Learning Engineer

Lynker

• 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.

Job 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

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