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Machine Learning Engineer Jobs in California, MD

Radiance Technologies

Data Scientist

Dahlgren, VA · On-site

In this role, you'll work alongside a multidisciplinary team of software engineers, fellow data ... machine learning techniques, and helping shape national defense strategies, this is your ...

Sabre Systems LLC

Data Analytics Engineer

Lexington Park, MD · On-site

$111K - $133K/yr

Work with data engineers & developers to acquire, process, and format data both at source and post ... Knowledge of advanced analytics principals (statistical modeling, machine learning, AI)

Motorola

Director of Computer Vision

California, MD · On-site

Our AI-powered security solutions integrate advanced video analytics, machine learning, and ... Technical Vision, Engineering Leadership, and Execution: Provide executive technical leadership to ...

Autodesk

Software Architect

California, MD · On-site +1

$143K - $256K/yr

Mentor developers on emerging and existing technologies, as well as career development paths ... Working knowledge of LLMs and machine learning, with an understanding of key concepts and hands-on ...

Bowhead

Senior Data Scientist

Patuxent River, MD · On-site

... programming languages and visualization software. Responsibilities * Oversees the application of data mining, data modeling, natural language processing, and machine learning to extract and analyze ...

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Showing results 1-20

All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in California, MD

Machine Learning Engineer information

See California, MD salary details

$30.2K

$123.4K

$185.4K

How much do machine learning engineer jobs pay per year?

As of Jul 4, 2026, the average yearly pay for machine learning engineer in California, MD is $123,398.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,300.00 and $148,500.00 per year, depending on experience, location, and employer.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-demand industries or companies can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially in tech giants or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as AI advances, as they develop and refine algorithms, models, and systems. Roles that require complex problem-solving, creativity, and domain expertise—such as healthcare professionals, data scientists, software developers, cybersecurity specialists, and AI ethics officers—are also expected to persist due to their reliance on human judgment and specialized knowledge. These jobs often involve skills that are difficult for AI to fully replicate or replace.

What Does a Machine Learning Engineer Do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What engineers make $300,000 a year?

Senior machine learning engineers and data scientists with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $300,000 or more annually, especially in high-cost-of-living areas or top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on business outcomes.

What are some common challenges faced by Machine Learning Engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

More about Machine Learning Engineer jobs
What cities near California, MD are hiring for Machine Learning Engineer jobs? Cities near California, MD with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you
Data Scientist

Data Scientist

Radiance Technologies

Dahlgren, VA • On-site

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 12 days ago

Job description

Radiance Technologies is a 100% employee-owned company where innovation, ownership, and collaboration are at the core of everything we do. We offer a standout benefits package-including competitive salaries, full health/dental/vision/life insurance, a generous 401(k), tuition reimbursement, and a supportive, growth-driven work environment.
We're looking for a Data Scientist to join our Enhanced Modeling and Simulation (M&S) team. In this role, you'll work alongside a multidisciplinary team of software engineers, fellow data scientists, and operations research analysts to support the Joint Warfare Analysis Center and other Department of Defense and Intelligence Community missions.
If you're passionate about extracting insights from complex data, applying cutting-edge machine learning techniques, and helping shape national defense strategies, this is your opportunity to make a difference.
Required Skills
  • Strong communication skills and ability to translate complex findings into clear, actionable insights
  • Self-starter with a collaborative mindset and high attention to detail
  • Active TS/SCI security clearance required

Required Experience
  • Minimum 3 years of experience in data science, analytics, or a related field
  • Knowledge of data normalization and handling large, complex, or incomplete datasets
  • Strong proficiency in Python and/or R (VBA or MATLAB experience a plus)
  • Experience visualizing analytical results and building compelling dashboards
  • Familiarity with constructive simulation systems (e.g., AFSIM, ITASE, NGTS)
  • Proven ability to perform advanced statistical modeling and experimentation

Desired Qualifications
  • Bachelor's degree or higher in Mathematics, Statistics, Computer Science, or a related discipline
    (with at least 30 semester hours in mathematics, statistics, or computer science)
  • Experience developing or enhancing cloud-based data solutions
  • Strong knowledge of data imputation techniques and applied machine learning
  • Familiarity with defense-related analytics or operational modeling preferred

At Radiance Technologies, your work has purpose. Join a team where your expertise in data science supports national security, drives innovation, and shapes the future of defense technology.
Radiance Technologies is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status.

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