1

Machine Learning R Jobs (NOW HIRING)

Proficiency in Python, R, Java, or similar programming languages used for machine learning and analytics development. * Experience with machine learning libraries and frameworks such as TensorFlow ...

SUMMARY The Machine Learning Engineer provides hands-on expertise in designing, implementing, and ... R, or Java • Experience with ML frameworks/libraries (TensorFlow, PyTorch, scikit-learn) • ...

Machine Learning Engineer

Austin, TX · On-site

$100 - $130/hr

Machine Learning Engineer page is loaded## Machine Learning Engineerlocations: Austin, TXtime type ... R, or Java • Experience with ML frameworks/libraries (TensorFlow, PyTorch, scikit-learn) • ...

Machine Learning Engineer

Aurora, CO · On-site

$120 - $180/hr

Proficiency in programming languages (e.g., Python, R, Java) * Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) * Expertise in model evaluation techniques and ...

Machine Learning Engineer

Reston, VA · On-site

$110 - $170/hr

Proficiency in programming languages (e.g., Python, R, Java) * Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) * Expertise in model evaluation techniques and ...

Proficiency in programming languages (e.g., Python, R, Java) * Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) * Expertise in model evaluation techniques and ...

Proficiency in programming languages (e.g., Python, R, Java) * Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) * Expertise in model evaluation techniques and ...

Proficiency in programming languages (e.g., Python, R, Java) * Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) * Expertise in model evaluation techniques and ...

Proficiency in programming languages (e.g., Python, R, Java) * Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) * Expertise in model evaluation techniques and ...

Proficiency in programming languages (e.g., Python, R, Java) * Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) * Expertise in model evaluation techniques and ...

Design and develop AI/ML solutions using Python and Visual Studio for back‑end machine learning ... Utilize tools like R, Angular, Go‑Lang, or similar for front‑end development. * Data Migration:

New

... Machine Learning R Forecasting Analytics Tableau Power BI Databases Data Analysis Computer Science Finance Python SQL Marketing Business Science Sales Management

Showing results 41-60

Machine Learning R information

See salary details

$25.5K

$42.6K

$88K

How much do machine learning r jobs pay per year?

As of Aug 21, 2026, the average yearly pay for machine learning r 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 is a machine learning r?

Machine Learning Engineers (R) are professionals who specialize in designing, building, and deploying machine learning models using the R programming language. They work with large datasets, develop algorithms, and use statistical methods to solve complex problems in areas like prediction, classification, and data analysis. Their responsibilities often include data preprocessing, model training and evaluation, and integrating machine learning solutions into production systems. R is particularly valued for its robust statistical libraries and data visualization capabilities, making it a popular choice for research and data science tasks.

What skills and qualifications are needed to thrive as a machine learning r?

To thrive as a Machine Learning Researcher, you need a strong background in mathematics, statistics, computer science, and a relevant advanced degree such as a master's or PhD. Proficiency in programming languages (like Python or R), machine learning frameworks (such as TensorFlow or PyTorch), and experience with data processing tools are typically required. Critical thinking, creativity, and effective communication are essential soft skills for developing novel solutions and collaborating with interdisciplinary teams. These skills and qualifications are crucial for driving innovation and solving complex real-world problems in the rapidly evolving field of machine learning.

What challenges do machine learning r face when transitioning models from research to production environments?

Machine Learning Researchers often encounter challenges when moving models from the experimental stage to production. These include ensuring the model generalizes well to real-world data, addressing issues with data drift, and optimizing computational efficiency for deployment. Collaboration with engineering and data teams is essential to adapt research prototypes to scalable, maintainable production systems. Gaining familiarity with deployment pipelines and monitoring tools can ease this transition and help bridge the gap between research and application.

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

AspectMachine Learning RData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related fields; certifications in ML or data analysisBachelor's or Master's in CS, Statistics, or related fields; certifications in data analysis or ML
Work EnvironmentTech companies, research labs, startups; focus on developing ML models using RVarious industries including finance, healthcare, tech; focus on data analysis, modeling, and insights
Industry UsageCommon in analytics and research roles using R for ML tasksBroader role including data cleaning, visualization, and strategic insights

While both roles involve data analysis and machine learning, Machine Learning R specialists focus specifically on developing ML models using R programming. Data Scientists have a broader scope, including data cleaning, visualization, and strategic decision-making across industries.

Is it possible to do machine learning in R?

Machine Learning R roles involve applying machine learning techniques using the R programming language, which offers numerous packages like caret, randomForest, and xgboost for model development. R is widely used in data analysis and statistical modeling, making it suitable for machine learning tasks in various industries. Proficiency in data manipulation, statistical concepts, and familiarity with R's ecosystem are essential for these roles.

Is machine learning R a high paying job?

Machine Learning R roles are generally well-paid due to the specialized skills required in data analysis, statistical modeling, and programming with R. Salaries depend on experience, location, and industry, but professionals with expertise in machine learning and R often earn above average tech salaries.
More about Machine Learning R jobs

What are the most commonly searched types of Machine Learning R jobs?

The most popular types of Machine Learning R jobs are:

Infographic showing various Machine Learning R job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 23% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.

Machine Learning Engineer

UNISSANT

Ashburn, VA • On-site

Full-time

Posted 17 days ago


Job description

Unissant, Inc. delivers innovative capabilities to the agencies that keep our nation healthy and safe. We apply our domain expertise, data acumen, and technology know-how to achieve breakthrough results for our clients. Working collaboratively, we advance missions and careers through a focus on honesty, integrity, and dependability. We continuously look for talent, excited to join that effort. To learn more about our exciting organization, please visit us at www.unissant.com.

We are seeking a Machine Learning Engineer to join our team and support our client in Ashburn, VA. The ideal candidate will bring hands-on experience in machine learning, advanced analytics, and AI-driven product development, with the ability to turn complex data into practical, mission-focused solutions. This role is well suited for a technically strong professional who enjoys building and improving models, partnering across Agile teams, and supporting the delivery of innovative capabilities from early concept through deployment and ongoing performance optimization.

Essential Duties and Responsibilities:

  • Design, develop, and maintain machine learning models that support a variety of AI applications.
  • Analyze large and complex datasets to identify trends, test hypotheses, and generate actionable insights using statistical and analytical methods.
  • Build and support reliable data pipelines that improve data quality, accessibility, and usability for machine learning and analytics initiatives.
  • Collaborate with data engineering and cross-functional teams to enhance data workflows and optimize supporting infrastructure.
  • Contribute to AI product development activities across the lifecycle, including prototyping, implementation, deployment, and post-production support.
  • Monitor model effectiveness and product performance metrics, and perform ongoing enhancements to improve accuracy, scalability, and reliability.
  • Work closely with product managers, developers, designers, and QA teams within a large Agile development environment.

Work Experience and Job Skills:

  • Three (3) to four (4) years of hands-on experience in machine learning engineering, AI solution development, data analytics, or related technical work is preferred.
  • Experience supporting AI, machine learning, or advanced analytics initiatives is required.
  • Demonstrated experience developing and deploying AI/ML models in a production environment.
  • Proficiency in Python, R, Java, or similar programming languages used for machine learning and analytics development.
  • Experience with machine learning libraries and frameworks such as TensorFlow, PyTorch, or Scikit-learn.
  • Familiarity with MLOps practices, CI/CD pipelines, and model deployment processes.
  • Working knowledge of SQL and NoSQL databases and data processing tools such as Apache Spark or Hadoop.
  • Experience with analytics and visualization tools such as Tableau, Power BI, matplotlib, or Plotly.
  • Exposure to cloud platforms such as AWS, Azure, or GCP for model deployment, storage, or related services is preferred.
  • Strong problem-solving abilities, attention to detail, and organizational skills.
  • Ability to manage multiple assignments independently while collaborating effectively across technical and business teams.
  • Experience working in Agile product development environments is a plus.

Education:

  • Bachelor's Degree in Computer Science, Data Science, Electrical Engineering, Physics, or a related technical field is required.
  • Master's Degree in a relevant field is preferred.
  • Equivalent combination of education and experience may be considered in lieu of strict degree requirements, based on client standards.

Certificates, Licenses and Registrations:

  • Relevant certifications in cloud computing, machine learning, data science, or data engineering are a plus.
  • Additional technical certifications may be considered based on program requirements.

Communication Skills:

  • Excellent verbal and written communication skills, with the ability to clearly explain technical concepts to both technical and non-technical audiences.
  • Strong interpersonal skills and the ability to collaborate effectively across cross-functional teams in a client-facing environment.

Clearance Requirements:

  • Ability to obtain and maintain a Public Trust position and favorable suitability determination based on a CBP background investigation is required.

Travel:

  • This is a hybrid position based in Ashburn, VA, with onsite support expected one to two days per week and additional onsite presence as required by mission needs.

Environmental Requirements:

  • Mainly a routine office environment.
  • May be required to lift up to ten (10) pounds.
  • Flexible in working extended hours.

The above statements are intended to describe the general nature and level of work being performed by the individual(s) assigned to this position. They are not intended to be an exhaustive list of all duties, responsibilities, and skills required. Unissant management reserves the right to modify, add, or remove duties and to assign other duties as necessary. In addition, where applicable and available, reasonable accommodation(s) may be made to enable individuals with disabilities to perform essential functions of this position.

Please note: Candidate(s) will be required to go through pre-employment screening.

Unissant, Inc. is a proud Equal Opportunity Employer! (EOE; M/F/Disability/Vets)