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Machine Learning R Jobs (NOW HIRING)

Point72

Machine Learning Engineer

New York, NY · On-site

Proficiency in programming languages such as Python and R * Experience with machine learning software libraries such as TensorFlow or PyTorch * Experience implementing Agent or Context engineering is ...

Daman Inc

Machine Learning Engineer

San Antonio, TX · On-site

Experience in using Python, R or Matlab is required * Industry experience as a Machine Learning Engineer * Knowledge of or experience in building production quality and large-scale deployment of ...

New

Point72

Machine Learning Engineer

New York, NY · On-site

Proficiency in programming languages such as Python and R * Experience with machine learning software libraries such as TensorFlow or PyTorch * Experience implementing Agent or Context engineering is ...

Howmet

Machine Learning Engineer

Whitehall, MI · On-site

Design, develop, and evaluate advanced deep learning architectures (e.g., CNNs, Mask R-CNNs, YOLO ... Build and refine machine learning algorithms to enhance Howmet products across all business units.

BeeGenius

AI/Machine Learning Engineer

Sunnyvale, CA · On-site

D. in Computer Science, Data Science, or a related field • Strong programming skills in Python or R • Experience with machine learning frameworks (e.g., TensorFlow, PyTorch) • Knowledge of ...

ManTech International

Machine Learning Engineer

$128K - $214K/yr

Train and embed machine learning models into applications using programming languages (Python, Java, R) and core libraries (TensorFlow, Keras, Scikit-learn). * Explore and visualize data to uncover ...

Factspan Inc

Machine Learning Engineer

Seattle, WA · On-site

Hands on expertise in Machine Learning models using R/Python, SQL, well versed in statistical methodology including deep expertise and experience with statistical data analysi * Requires a ...

Factspan Inc

Machine Learning Engineer

Seattle, WA · On-site

Hands on expertise in Machine Learning models using R/Python, SQL, well versed in statistical methodology including deep expertise and experience with statistical data analysi * Requires a ...

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Machine Learning R information

See salary details

$25.5K

$42.6K

$88K

How much do machine learning r jobs pay per year?

As of Sep 11, 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.
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Machine Learning R jobs near you
Infographic showing various Machine Learning R job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 74% Full Time, 22% Part Time, and 2% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.

Machine Learning Engineer

Pleasanton, CA • On-site

Indotronix International Corporation
Recruiting and Staffing Services • 1 - 5K employees
Learn more about Indotronix International Corporationexternal

Contractor

Re-posted 17 days ago

Job description

Machine Learning Engineer (Azure Focus) - Remote (PST)
[About the Role]
Join GAP as a Machine Learning Engineer and lead the development, deployment, and optimization of innovative AI solutions in a fully remote environment. This six-month contract opportunity is tailored for engineers with a passion for hands-on machine learning in Microsoft Azure production settings. Collaborate with talented teams to create real business impact by delivering robust, scalable models for enterprise applications.
[Responsibilities]
- Design, build, and deploy machine learning models using neural networks and NLP techniques to solve business challenges
- Manage the complete ML lifecycle: data preparation, model selection, training, evaluation, deployment, and ongoing performance monitoring
- Leverage Python and ML frameworks (TensorFlow, PyTorch, Keras) to develop, optimize, and maintain models
- Implement MLOps best practices, including CI/CD pipelines, model versioning, and automated retraining in Azure environments
- Collaborate cross-functionally with data scientists, engineers, and stakeholders to deliver production-ready AI solutions
- Utilize Azure Machine Learning, Azure DevOps, and Azure Databricks for end-to-end ML operations
[Required Skills and Experience]
- Proven track record developing and deploying machine learning models into Microsoft Azure cloud platforms
- Hands-on expertise with neural networks and NLP methods (text classification, sentiment analysis, entity extraction, chatbots, or language models)
- Advanced proficiency in Python; practical experience with R and SQL for data extraction and statistical modeling
- Deep understanding of supervised and unsupervised learning algorithms, model evaluation, and optimization
- Mastery of modern ML frameworks (TensorFlow, PyTorch, Keras) in production
- Demonstrable experience in MLOps: CI/CD for ML, model monitoring, version control, retraining, and production support
[Preferred Skills]
- Experience with Azure Databricks, Azure Functions, and Azure Pipelines
- Familiarity with containerization (Docker/Kubernetes) for scalable ML deployments
- Strong feature engineering and ML pipeline automation skills
[Benefits]
- 100% remote work-collaborate with a diverse team from anywhere within PST hours
- Opportunity for contract extension and career progression on impactful enterprise AI projects
- Exposure to best-in-class Azure ML infrastructure and enterprise DevOps practices
[How to Apply]
Excited to build and deploy cutting-edge AI solutions in Azure? Submit your resume now. Qualified candidates will be contacted for an initial screening and technical interview.
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About Indotronix

Sourced by ZipRecruiter

In 1986, Indotronix established itself in the staffing space. 22 years later, Avani entered the scene, offering consulting and technology development. Finally, in 2016, the two joined forces to begin delivering talent across all areas, from Staffing to Consulting to unique platform development.

Industry

Recruiting and staffing services

Company size

1,001 - 5,000 Employees

Headquarters location

Rochester, NY, US

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