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Machine Learning Operations Jobs in Maryland (NOW HIRING)

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Machine Learning Operations information

Is ML a high paying job?

Machine Learning Operations (MLOps) roles are generally well-paid due to the specialized skills required, such as expertise in cloud platforms, programming, and data management. Salaries tend to be higher than average tech roles and can increase with experience, certifications, and knowledge of tools like TensorFlow or Kubernetes.

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

AspectMachine Learning OperationsData Scientist
Primary FocusDeploying, maintaining, and scaling ML models in productionAnalyzing data to develop insights and build models
Required SkillsML deployment, cloud platforms, automation, scriptingStatistical analysis, data visualization, programming (Python/R)
Work EnvironmentOperations teams, cloud infrastructure, production systemsResearch environments, data analysis teams, R&D
Common CertificationsCloud certifications, MLOps tools certificationsData science certifications, statistical courses

Machine Learning Operations and Data Scientists often collaborate, but MLOps focuses on deploying and maintaining models in production, while Data Scientists focus on analyzing data and developing models. Both roles require technical skills, but their day-to-day tasks and environments differ.

What engineer makes $500,000 a year?

Senior machine learning operations engineers with extensive experience, advanced skills in automation, cloud platforms, and deployment pipelines can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or large tech companies. Such roles often require expertise in tools like Kubernetes, Docker, and cloud services, along with strong problem-solving and leadership abilities.

What is a $900000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers, AI research directors, or chief AI officers, often requiring advanced skills in machine learning, deep learning, and data science. These positions usually involve leadership responsibilities, extensive experience, and may include stock options or bonuses that contribute to the total compensation. Such roles are rare and highly competitive, often found in large tech companies or innovative startups.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and maintain AI systems, and while AI automation tools can handle certain tasks, MLEs are essential for creating, tuning, and overseeing complex models. AI may automate some routine aspects, but MLEs' expertise in data engineering, model optimization, and deployment remains critical for effective AI solutions.
What cities in Maryland are hiring for Machine Learning Operations jobs? Cities in Maryland with the most Machine Learning Operations job openings:
Machine Learning Operations jobs near you
Infographic showing various Machine Learning Operations job openings in Maryland as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.
Research Associate, Atmospheric Science, Machine Learning

Research Associate, Atmospheric Science, Machine Learning

DeVine Consulting, Inc.

Silver Spring, MD • On-site

Full-time

Posted 8 days ago

Job description

Job Summary:
DeVine Consulting, Inc. provides technical and scientific support to government clients in Oceanography & Atmospheric Science. They are seeking a Research Associate with experience in Atmospheric Science and Machine Learning to support a government customer, focusing on improving weather forecast performance.
Responsibilities:
• Conduct innovative research at the intersection of weather prediction and machine learning, including approaches that leverage observations from satellite constellation
• Develop, verify, and document forecast improvements that provide measurable value to customers
• Partner with engineering and product teams to transition research advances into scalable, operational systems
• Communicate results through internal reviews, customer discussions, and, where appropriate, conferences or publications
• Contribute broadly to improving forecasts and overall product performance
Qualifications:
Required:
• Graduate degree in atmospheric science, meteorology, computer science, or a related field
• 2+ years of experience developing ML models for weather applications
• Strong ML engineering fundamentals, including model training, validation, evaluation, and documentation
• Training, running, and verifying AI-based weather prediction models
• Working in cloud-based computing environments
• Handling large meteorological datasets and common data formats at scale
• Modern deep learning frameworks (e.g., PyTorch or TensorFlow)
• Large geophysical dataset formats (GRIB, NetCDF, ZARR)
• Proficiency with deep learning frameworks (e.g., PyTorch, TensorFlow)
• Familiarity with cloud-based computing environments (AWS, GCP, Azure)
• Strong written and verbal communication skills
• Ability to manage multiple projects and balance competing priorities
Company:
DeVine Consulting, Inc. Founded in 1998, the company is headquartered in Fremont, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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