AI Scientist/Engineer - NOAA Meteorological focus

ZipRecruiter; Baltimore (MD); Remote; USD 100,000 - 150,000; Full time

Job summary

A leading company in environmental data science is seeking an AI Scientist/Engineer to develop advanced AI/ML models tailored to environmental challenges. The ideal candidate will have a strong background in meteorology or earth sciences, with proven experience in machine learning and data pipeline engineering. This remote position offers the opportunity to work on impactful projects with domain experts.

Qualifications

• 5+ years of experience building and deploying ML models.
• Strong understanding of meteorology and climate science.
• Advanced skills in Python and ML frameworks.

Responsibilities

• Design, build, and deploy machine learning models for environmental challenges.
• Develop multi-class classification systems for weather and climate data.
• Build and analyze knowledge graphs for environmental relationships.

Skills

Machine Learning

Deep Learning

Natural Language Processing

Geospatial Analysis

Data Pipeline Engineering

Education

Bachelor's or Master's in relevant field

Tools

Python

PyTorch

TensorFlow

scikit-learn

Job description

Job Description

Role: AI Scientist/Engineer

Company: Arch Systems

Location: Remote

Employment Type: Full-Time

Position Overview

Arch Systems is seeking a highly skilled and motivated AI Scientist/Engineer with a strong background in meteorology, earth sciences, or environmental data science. Experience working with NOAA data systems, modeling frameworks, or research initiatives is highly valued. In this role, you will design and implement sophisticated AI/ML models tailored to large-scale, domain-specific challenges in taxonomy, entity resolution, pattern recognition, and knowledge graph construction — all in the context of environmental, meteorological, or geospatial data.

Responsibilities

• Model Development: Design, build, and deploy machine learning models addressing meteorological, climatological, or earth science-related challenges including taxonomy extraction, entity resolution, and pattern recognition.
• Environmental AI Applications: Develop multi-class classification systems for weather, climate, and earth science data.
• Knowledge Graph Construction: Build and analyze knowledge graphs that map complex environmental relationships, phenomena, and classifications.
• NLP for Science Domains: Apply natural language processing techniques to scientific literature, metadata, and environmental reports (e.g., topic modeling, semantic search).
• Document Clustering and Summarization: Lead efforts in clustering, classifying, and summarizing scientific documents and environmental datasets.
• Data Pipeline Engineering: Build and optimize large-scale, robust data pipelines to support mission-critical environmental and meteorological data operations.
• Applied Research: Contribute to applied AI/ML research initiatives that enhance environmental situational awareness, risk modeling, and predictive analytics.
• Collaboration: Work closely with domain experts, data engineers, and project managers to translate scientific and operational requirements into scalable AI-driven solutions.
• Continuous Innovation: Stay abreast of emerging technologies in AI/ML, meteorology, earth science, and environmental informatics.

Qualifications

Experience:

• 5+ years of experience building and deploying ML models in production environments.
• Hands-on experience working with NOAA, NWS, NESDIS, NCEI, or related meteorological/earth science organizations.

Domain Knowledge:

• Strong understanding of meteorology, climate science, geospatial analysis, or earth systems science.
• Familiarity with environmental and meteorological datasets (e.g., satellite data, weather forecasts, climate models).

Technical Expertise:

• Deep knowledge of machine learning, deep learning methodologies, and applied AI research.
• Experience with NLP, semantic retrieval, and large models (LLMs) in scientific domains.

Programming and Tools:

• Advanced skills in Python, with expertise in ML frameworks like PyTorch, TensorFlow, and scikit-learn.
• Experience handling large-scale, complex scientific datasets and building sophisticated data pipelines.

Solution Development:

• Proven ability to turn complex environmental or scientific challenges into elegant, production-ready solutions.

Company Description

HIGH Growth, small business. Check us out at https://archsystemsinc.com/

Arch Systems LLC is committed to diversity in its workforce and is proud to be an equal opportunity employer. We consider qualified applicants without regard to race, color, religion, sex, national origin, veteran status, marital status, age, disability, gender identity, sexual orientation, or any other legally protected class.