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Ocean Machine Learning Jobs (NOW HIRING)

Machine Vision Engineer

Hickory, NC · On-site

$88K - $121K/yr

From the depths of the ocean to the farthest reaches of space, our technologies push the boundaries ... Artificial intelligence and machine learning applied to vision systems. This position does not ...

Machine Vision Engineer

Hickory, NC · On-site

$88K - $121K/yr

From the depths of the ocean to the farthest reaches of space, our technologies push the boundaries ... Artificial intelligence and machine learning applied to vision systems. This position does not ...

Machine Vision Engineer

Hickory, NC · On-site

$88K - $121K/yr

From the depths of the ocean to the farthest reaches of space, our technologies push the boundaries ... Artificial intelligence and machine learning applied to vision systems. This position does not ...

Machine Vision Engineer

Hickory, NC · On-site

$88K - $121K/yr

From the depths of the ocean to the farthest reaches of space, our technologies push the boundaries ... Artificial intelligence and machine learning applied to vision systems. This position does not ...

Redshift, S3, Spark, Digital Ocean, etc. Should have experience Supporting on Vector Machine methods Experience creating and using advanced machine learning algorithms and statistics: regression ...

... ocean, and even roamed Disney Parks. Our mission is focused squarely on shipping beautiful ... Machine Learning : Implement learning algorithms, training pipelines, and model optimization for ...

Sr. Engineer, Machine Vision

Corning, NY · On-site

$95K - $131K/yr

From the depths of the ocean to the farthest reaches of space, our technologies push the boundaries ... Utilize novel computer vision and machine learning methods to perform object detection ...

Sr. Engineer, Machine Vision

Corning, NY · On-site

$95K - $131K/yr

From the depths of the ocean to the farthest reaches of space, our technologies push the boundaries ... Utilize novel computer vision and machine learning methods to perform object detection ...

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Ocean Machine Learning information

See salary details

$25.5K

$42.6K

$88K

How much do ocean machine learning jobs pay per year?

As of Jun 4, 2026, the average yearly pay for ocean machine learning in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Ocean Machine Learning Specialist, and why are they important?

To excel as an Ocean Machine Learning Specialist, you need a strong background in data science, oceanography, and programming, typically supported by a degree in computer science, marine science, or a related field. Familiarity with machine learning frameworks (such as TensorFlow or PyTorch), oceanographic data platforms, and programming languages like Python or R is essential. Strong analytical thinking, problem-solving abilities, and effective communication skills set top professionals apart in this field. These skills are crucial for accurately interpreting complex ocean data, developing predictive models, and collaborating with interdisciplinary teams to address marine challenges.

What are some common challenges faced by professionals working in ocean machine learning, and how can they be addressed?

Professionals in ocean machine learning often encounter challenges such as limited availability of high-quality labeled data, dealing with noisy or incomplete datasets from ocean sensors, and adapting machine learning models to complex, dynamic marine environments. Addressing these issues often involves collaborating closely with oceanographers and data engineers to improve data collection methods, applying advanced data pre-processing techniques, and leveraging domain-specific knowledge to inform model development. Staying current with the latest research and participating in interdisciplinary teams can also help overcome these unique obstacles and drive innovation in the field.

What is an Ocean Machine Learning specialist?

An Ocean Machine Learning specialist is a professional who applies machine learning techniques to analyze and interpret oceanographic data. They work with large and complex datasets gathered from sources like satellites, underwater sensors, and robotic vehicles to study ocean patterns, marine life, climate change, and environmental impacts. Their work helps improve predictive models for weather, ocean currents, and marine ecosystem health, contributing valuable insights for scientific research, conservation, and maritime industries.

What is the difference between Ocean Machine Learning vs Ocean Data Scientist?

AspectOcean Machine LearningOcean Data Scientist
Required CredentialsDegree in Computer Science, Data Science, or related fields; knowledge of ML frameworksDegree in Data Science, Statistics, or related fields; strong programming skills
Work EnvironmentResearch labs, tech companies, marine research institutionsResearch institutions, environmental agencies, marine industry
Industry UsageDeveloping ML models for ocean data analysisAnalyzing ocean data to inform decisions and research

Ocean Machine Learning focuses on developing algorithms and models to analyze ocean data, often requiring advanced programming and ML expertise. Ocean Data Scientists interpret ocean data to generate insights, combining statistical analysis with domain knowledge. Both roles overlap in skills but differ in their primary focus: model development versus data interpretation.

Infographic showing various Ocean Machine Learning job openings in the United States as of May 2026, with employment types broken down into 2% Locum Tenens, 4% Internship, 45% Full Time, 31% Part Time, 13% Contract, and 5% Nights. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.
AI Models for Earthsystem

AI Models for Earthsystem

Argonne National Laboratory

Springfield, IL • On-site

$94K - $147K/yr

Full-time

This job post has expired today. Applications are no longer accepted.


Job description

Argonne National Laboratory, a U.S. Department of Energy national laboratory located near Chicago, Illinois, has an opening for a highly motivated term position in the Decision & Infrastructure Sciences Division. Machine learning (ML), specifically deep learning (DL) an AI foundation models, has demonstrated success in predicting weather for 1-14 days with skill on par with numerical weather prediction. Recently Argonne successfully implemented, AI foundation models for medium range weather forecasting (STORMER) and AERIS, a state-of-the-art Seasonal-to-sub-seasonal weather model AI model.

A successful candidate will collaborate with this group to further develop AERIS, coupling the model with ocean and land components, data assimilation, multi-modality and regional refinement. In particular, this position will utilize generative AI transformer model to create a calibrated ensemble system for S2S at high resolution (30-km and finer) to deliver probabilistic weather forecasts beyond 14 days to allow for actionable, local-scale impacts on infrastructure and communities.

The ideal candidate has a PhD in geophysical sciences, computer science, or machine learning with experience in developing and verifying deep learning-based models for large dynamical systems (e.g. weather). Some familiarity in data and model parallelisms for distributed training on large GPU-based machines is essential. who have experience with diffusion-based or other generative AI methods and multi-modal embeddings, as well as a background in atmospheric science, especially weather modeling.

Responsibilities:

  • Contributes technical experience through analysis and support for programs and projects associated with machine learning, HPC, and computational problems related to earth system science and other dynamical systems.
  • Develops and evaluates machine learning/computational approaches, synthesis activities, computational tools, compiling results, contributes to reports, publications, and documentation.
  • In particular, this position will assist on projects related to applying and developing machine learning-based weather models for the S2S time frame with an emphasis on generative AI techniques, evaluating such models, and working with a team of scientists.

Position Requirements

  • Experience with deep learning, PyTorch/ JAX, and scaling deep learning models to large GPU-based machines.
  • Experience building, training and running inferences with large AI foundation models for science domain.
  • Technical knowledge in using HPC systems for visualization and analysis.
  • Knowledge of large, dynamical systems (preferably the atmosphere), is desirable.
  • Skills in clear, concise writing of technical papers, and interacting and communicating effectively with colleagues.
  • Some problem-solving skills.
  • Organizational skills and flexibility in coordinating a broad spectrum of activities.
  • Knowledge of atmospheric dynamics, process scale models, and numerical computation techniques is preferred.
  • Experience in scientific programming and data analysis.
  • Knowledge of using atmospheric observational datasets, data assimilation techniques, and statistics is preferred.
  • Familiarity sub-seasonal-to-seasonal modeling and or coupled atmosphere-ocean modeling is desirable.
  • Ability to work and communicate with stakeholders from public and private sectors.
  • Ability to model Argonne's core values of impact, safety, respect, integrity, and teamwork.

Minimum Education/Experience Requirements: PhD Degree or their equivalents in geophysical sciences, computer science, machine learning, or a related field.

Job Family

Research Development (RD)

Job Profile

Atmospheric & Earth Science 2

Worker Type

Long-Term (Fixed Term)

Time Type

Full time

The expected hiring range for this position is $94,486.00 - $147,398.94.

Please note that the pay range information is a general guideline only. The pay offered to a selected candidate will be determined based on factors such as, but not limited to, the scope and responsibilities of the position, the qualifications of the selected candidate, business considerations, internal equity, and external market pay for comparable jobs. Additionally, comprehensive benefits are part of the total rewards package.

Click here (https://www.anl.gov/hr/healthcare-insurance) to view Argonne employee benefits!

As an equal employment opportunity employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a safe and welcoming workplace that fosters collaborative scientific discovery and innovation. Argonne encourages everyone to apply for employment. Argonne is committed to nondiscrimination and considers all qualified applicants for employment without regard to any characteristic protected by law.

Argonne employees, and certain guest researchers and contractors, are subject to particular restrictions related to participation in Foreign Government Sponsored or Affiliated Activities, as defined and detailed in United States Department of Energy Order 486.1A. You will be asked to disclose any such participation in the application phase for review by Argonne's Legal Department.

All Argonne offers of employment are contingent upon a background check that includes an assessment of criminal conviction history conducted on an individualized and case-by-case basis. Please be advised that Argonne positions require upon hire (or may require in the future) for the individual be to obtain a government access authorization that involves additional background check requirements. Failure to obtain or maintain such government access authorization could result in the withdrawal of a job offer or future termination of employment.