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Data Scientist Machine Learning Engineer Jobs (NOW HIRING)

Roberts Recruiting

Senior Data Scientist

Boston, MA

This is an exciting Senior Data Scientist/Machine Learning opportunity to have a real impact and be ... Work with our product managers and machine learning engineers during development phase. Nice-to ...

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Data Scientist Machine Learning Engineer information

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

As of Jun 25, 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 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.

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

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.

What engineers make $500,000?

Data Scientist and Machine Learning Engineer roles can reach $500,000 annually, especially with extensive experience, advanced skills in programming, statistical analysis, and familiarity with tools like Python, R, and cloud platforms. Compensation often includes base salary, bonuses, and stock options, particularly in high-demand industries or senior positions.

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.

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.

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 and algorithms; however, machine learning engineers typically require stronger software engineering skills, experience with deployment, and knowledge of tools like cloud platforms and APIs. Many professionals develop these skills through additional training or certifications to move between these roles.

Is 40 too late for data science?

Data scientists and machine learning engineers can successfully enter the field at age 40 or older, as skills in programming, statistics, and domain knowledge are more important than age. Many professionals transition into data science later in their careers by acquiring relevant certifications, such as those in Python, R, or machine learning, and building a strong portfolio. Age is generally not a barrier if you are committed to continuous learning and adapting to evolving tools and techniques.

Which 5 jobs will survive AI?

Data Scientist and Machine Learning Engineer roles are expected to persist as they involve complex problem-solving, domain expertise, and developing new algorithms that AI cannot fully replicate. Jobs requiring creativity, emotional intelligence, and strategic decision-making, such as healthcare professionals, educators, and specialized technical roles, are also likely to endure. Continuous learning and adapting to new tools like AI frameworks will be essential for these careers.
More about Data Scientist Machine Learning Engineer jobs
What job categories do people searching Data Scientist Machine Learning Engineer jobs look for? The top searched job categories for Data Scientist Machine Learning Engineer jobs are:
Data Scientist Machine Learning Engineer jobs near you
Data Scientist/Machine Learning Engineer

Data Scientist/Machine Learning Engineer

CATHEXIS

Redwood City, CA • On-site

$125K - $150K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 28 days ago

Job description

Team CATHEXIS elevates the government contracting experience through rapid response, deep skill, and thoughtful problem-solving and communication. Our core capabilities are our top-tier program and project management, data analytics, and audit services, the backbone of which is our integrated approach to operational excellence.

You worked hard to get to where you are. You strive to make every day better than the day before. So do we. Team CATHEXIS operates with an all-in mindset. We are working together to create a company that supports our shared values and individual goals. Our values are centered around leading with integrity, owning the outcome, growing together, and moving with purpose in everything we do for our employees, customers, partners, and communities. We believe success is best when we listen and lead with empathy; model high standards of ethics to provide a rewarding candidate experience; work hard, have fun, and appreciate the strengths we all bring to the team; and empower our employees to create innovative and trusted results.

We are looking for a dynamic Data Scientist/ML Engineer to join our team. The Data Scientist/ML Engineer will work directly with data scientists, software engineers, and subject matter experts in the definition of new analytics capabilities able to provide our federal customers with the information they need to make proper decisions and enable their digital transformation.

We are proactively building a pipeline of qualified candidates for future opportunities that may arise. If your background aligns with our anticipated needs, a member of our Talent Acquisition team may reach out should a role become available or to proactively screen you for the role.

Responsibilities

The responsibilities include, but are not limited to:

  • Research, design, implement, and deploy Machine Learning algorithms for enterprise applications.
  • Assist and enable federal customers to build their own applications.
  • Contribute to the design and implementation of new features.

Requirements

  • Bachelor's degree in Computer Science, Electrical Engineering, Statistics, or equivalent fields required.
  • MS or PhD in Computer Science, Electrical Engineering, Statistics, or equivalent fields preferred.
  • Minimum 2 years relevant work experience preferred.
  • Excellent programming skills in Python.
  • Applied Machine Learning experience (regression and classification, supervised, and unsupervised learning).
  • Strong mathematical background (linear algebra, calculus, probability, and statistics).
  • Experience with scalable ML (MapReduce, streaming).
  • Ability to drive a project and work both independently and in a team.
  • Smart, motivated, can-do attitude, and seeks to make a difference.
  • Excellent verbal and written communication.
  • Real passion for developing team-oriented solutions to complex engineering problems.
  • Thrive in an autonomous, empowering and exciting environment.
  • Great verbal and written communication skills to collaborate multi-functionally and improve scalability.
  • Interest in committing to a fun, friendly, expansive, and intellectually stimulating environment.
  • Convey highly technical concepts and information in written form to technical and non-technical audiences.
  • The ability to work on multiple concurrent projects is essential.
  • Strong self -motivation and the ability to work with minimal supervision.
  • Must be a team-oriented individual, energetic, result & delivery oriented, with a keen interest on quality and the ability to meet deadlines.
  • Ability to work in an agile environment.
Desired Skills
  • Hands-on experience deploying and operating applications using IaaS and PaaS on major cloud providers, such as Amazon AWS, Microsoft Azure, or Google Cloud Services.
  • Experience with deep learning, natural language processing, computer vision, or reinforcement learning.

Benefits

CATHEXIS offers competitive compensation packages to all eligible employees. Our goal is to provide a compensation package that reflects the value you bring to our team, is competitive with national average market rates, and promotes your financial security and personal well-being. The annual salary range for this role is $125,000 - $150,000. Please note that the salary information provided is a general guideline. CATHEXIS considers various factors in its final offer, including location, qualifications, experience, and skills.

  • Performance Bonuses
  • Medical Insurance
  • Dental Insurance
  • Vision Insurance
  • 401(k) Plan (Traditional and ROTH)
  • Life Insurance (Basic, Voluntary & AD&D)
  • Paid Time Off
  • 11 Federal Holidays
  • Parental Leave
  • Commute Benefits
  • Short Term & Long Term Disability
  • Training & Development
  • Wellness Program
  • Community Outreach Initiatives

CATHEXIS is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or protected veteran status and will not be discriminated against on the basis of disability EEO IS THE LAW. If you are an individual with a disability and would like to request a reasonable accommodation as part of the employment selection process, please contact the Recruiting Department RecruitingTeam@cathexiscorp.com