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Data Scientist Machine Learning Engineer Jobs (NOW HIRING)

IQUASAR LLC

DATA SCIENTIST

San Diego, CA · On-site

$120K - $150K/yr

Data Scientist (Machine Learning Engineer) Location: San Diego, CA Clearance Level: Secret iQuasar is seeking a highly motivated Data Scientist/Machine Learning Engineer to join our dynamic AI team.

iQuasar LLC

DATA SCIENTIST

San Diego, CA · On-site

$120K - $150K/yr

Data Scientist (Machine Learning Engineer) Location: San Diego, CA Clearance Level: Secret iQuasar is seeking a highly motivated Data Scientist/Machine Learning Engineer to join our dynamic AI team.

Rule14

Data Scientist Machine Learning

Santa Monica, CA · On-site

$75K - $100K/yr

As a Data Scientist Machine Learning, you will work within a small data science team focusing on ... Perform feature engineering to enhance model performance * Select appropriate algorithms based on ...

York Solutions, LLC

Data Scientist

Minnetonka, MN · On-site

Hybrid onsite Tuesday Wednesday and Thursday Data Scientist / Machine Learning Engineer Position Overview As a Data Scientist / Machine Learning Engineer on our AI Builder program, you will design ...

Team Velocity Marketing

$160K - $190K/yr

Senior Data Scientist - Machine Learning & AI Senior Data Scientist - Machine Learning & AI Remote ... You will partner with Product, Data Engineering, Software Engineering, Analytics, and business ...

Merican

Data Science & Machine Learning Engineer

$117K - $140K/yr

Senior Data Science & Machine Learning Engineer Location: Remote, USA (Client Location ZIP: 01730) Duration: 6 Months Contract to Hire We are seeking an experienced Senior Data Science & Machine ...

Socket.dev

Machine Learning Engineer

Los Angeles, CA · On-site

Role Description Founding Data Scientist / Machine Learning Engineer We're looking for a highly ambitious Data Scientist to help build the predictive intelligence layer behind nowfluence. This is not ...

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Data Scientist Machine Learning Engineer information

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$46K

$165K

$243.5K

How much do data scientist machine learning engineer jobs pay per year?

As of Sep 15, 2026, the average yearly pay for data scientist machine learning engineer in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What is a data scientist machine learning engineer?

A Data Scientist Machine Learning Engineer is a professional who combines expertise in data analysis, statistical modeling, and software engineering to design, build, and deploy machine learning models. They work with large datasets to extract insights and solve complex problems by developing algorithms and predictive models. In addition to building models, they are responsible for ensuring models are scalable, robust, and integrated into production systems, often collaborating with data engineers and business stakeholders.

What are the key skills and qualifications needed to thrive as a data scientist machine learning engineer?

To thrive as a Data Scientist Machine Learning Engineer, a strong background in statistics, programming (Python, R), and machine learning algorithms is essential, typically supported by a degree in computer science, mathematics, or a related field. Familiarity with tools like TensorFlow, PyTorch, scikit-learn, and experience with big data platforms (Spark, Hadoop) and cloud services (AWS, Azure) are commonly required. Strong problem-solving abilities, communication skills, and a collaborative mindset help professionals translate complex data insights into actionable business solutions. These skills are crucial for effectively designing, deploying, and explaining machine learning models that drive innovation and informed decision-making.

How do data scientist machine learning engineers typically collaborate with other departments within an organization?

Data Scientist Machine Learning Engineers often work closely with cross-functional teams such as software engineers, product managers, and domain experts. They collaborate to understand business requirements, gather and preprocess data, and integrate machine learning models into production systems. Regular communication is essential to ensure that developed solutions align with organizational goals and are scalable. This collaborative environment not only helps in building robust models but also enhances the engineer’s understanding of real-world business challenges.

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

AspectData Scientist Machine Learning EngineerData Analyst
Required CredentialsDegree in CS, Data Science, or related; experience with ML frameworksDegree in Statistics, Math, or related; proficiency in data visualization tools
Work EnvironmentDevelops ML models, algorithms, and scalable solutionsAnalyzes data, creates reports, and visualizations
Industry UsageTech, finance, healthcare, and more; focus on predictive modelingBusiness, marketing, finance; focus on reporting and insights

While Data Scientists Machine Learning Engineers focus on building and deploying machine learning models, Data Analysts primarily interpret data through reports and visualizations. Both roles require strong analytical skills, but Data Scientists Machine Learning Engineers typically have more technical expertise in algorithms and coding, making them more involved in model development and deployment.

Can a data scientist work as a machine learning engineer?

A data scientist can transition to a machine learning engineer role since both involve working with data, algorithms, and statistical models. However, machine learning engineers typically require stronger software engineering skills, experience with deployment, and knowledge of tools like cloud platforms and version control. Gaining expertise in programming, system design, and production environments is often necessary for this transition.
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What are popular job titles related to Data Scientist Machine Learning Engineer jobs?

For Data Scientist Machine Learning Engineer jobs, the most frequently searched job titles are:

Infographic showing various Data Scientist Machine Learning Engineer job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 84% Full Time, 12% Part Time, and 2% Contract. Highlights an 85% Physical, 3% Hybrid, and 12% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.

Data Scientist / Machine Learning Engineer

San Diego, CA • On-site

TransMedics, Inc.
Medical Equipment and Supplies Manufacturing • 501 - 1,000 employees
Learn more about TransMedics, Inc.external

Other

Medical, Vision, Life, Retirement, PTO

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

Data Scientist / Machine Learning Engineer

Data Scientist / Machine Learning Engineer

About TRABUS Technologies

TRABUS Technologies (TRABUS) is a minority-owned, Service-Disabled Veteran-Owned Small Business (SDVOSB) headquartered in San Diego, California. Since 2010, TRABUS has provided advanced wireless technology solutions, cybersecurity expertise, artificial intelligence capabilities, and engineering support to federal and commercial clients.

Recognized on the Inc. 5000 list for seven consecutive years, TRABUS is a dynamic, forward-leaning organization committed to solving complex, real-world challenges and delivering mission-ready solutions that meet and exceed customer expectations.

Position Overview

TRABUS Technologies is seeking a highly motivated Data Scientist / Machine Learning Engineer to join our growing Artificial Intelligence and Data Science team.

In this role, you will combine machine learning, data science, and software engineering skills to support a variety of AI-based projects, including resource planning for ship maintenance, marine transportation, and climate and environmental informatics.

The successful candidate will develop machine learning models that provide predictive insights and analytics for robust, web-based, full-stack AI applications supporting both government customers — including the Department of Defense (DoD), Department of Transportation (DoT), and National Oceanic and Atmospheric Administration (NOAA) — and commercial customers.

Key Responsibilities
  • Develop code to extract, clean, transform, and preprocess training datasets from disparate data formats, sources, and APIs.
  • Research, evaluate, select, and develop appropriate Machine Learning (ML) and Deep Learning (DL) algorithms and models.
  • Apply AI/ML techniques across diverse data domains, including Navy, transportation, environmental sciences, healthcare, and public safety.
  • Collaborate with the TRABUS Data Science team to develop scalable AI solutions incorporating technologies such as:
  • Retrieval-Augmented Generation (RAG)
  • Prompt Engineering
  • Computer Vision
  • Natural Language Processing (NLP)
  • Work alongside AI/ML and DevOps engineers to develop automated AI workflows that continuously generate predictions and inferences.
  • Develop validation and testing routines to measure model performance and evaluate the quality and accuracy of predictions.
  • Analyze large datasets and data streams to identify patterns, trends, and actionable insights.
  • Support the integration of machine learning models into web-based and full-stack AI applications.
  • Collaborate with technical teams throughout the development, testing, integration, and deployment lifecycle.
Required Qualifications
  • Minimum of 2 years of programming experience using Python.
  • Completed coursework in Machine Learning, Deep Learning, Algorithm Design, and Data Science.
  • Knowledge and experience with Python data science and machine learning libraries such as:
  • TensorFlow
  • PyTorch
  • Strong Python programming skills with the ability to process and analyze large datasets and data streams.
  • Understanding of databases, data structures, and API-based ETL operations.
  • Strong working knowledge of Linux or Unix-based operating systems.
  • Familiarity with Python web frameworks such as FastAPI, Django, and Flask.
  • Experience working with Git repositories and version control.
  • Ability to work collaboratively within multidisciplinary technical teams.
  • U.S. Citizenship is required.
  • Must be able to obtain and maintain a final DoD-adjudicated Secret security clearance.
Desired Qualifications
  • Current DoD-adjudicated Secret security clearance.
  • Strong knowledge of DevOps tools, processes, and best practices.
  • Experience working with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform.
  • Familiarity with Agile software development methodologies.
  • Experience working within Agile development environments.
  • Experience with Continuous Integration/Continuous Deployment (CI/CD) pipelines.
  • Proficiency with Microsoft Office applications.
  • Strong written and verbal communication skills.
  • Strong attention to detail and commitment to procedural compliance.
  • Ability to manage multiple responsibilities and priorities while meeting established deadlines.
Education
  • Bachelor's degree in Computer Science, Computer Engineering, Data Science, or another related STEM discipline.
  • Master's degree preferred.
Benefits

TRABUS Technologies offers a competitive compensation package and comprehensive employee benefits, including:

  • Paid Time Off (PTO)
  • Paid Holidays
  • Health Insurance
  • Vision Insurance
  • Flexible Spending Account (FSA)
  • 401(k)
  • Life and AD&D Insurance
Equal Employment Opportunity

TRABUS Technologies is an Equal Employment Opportunity Employer. We are committed to the principles of equal employment opportunity and will not discriminate against any employee or applicant for employment because of race, color, religion, sex, national origin, age, disability, veteran status, or any other status protected by applicable federal, state, or local discrimination laws.

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