ZipRecruiter

Log In

1

Machine Learning Engineer Jobs in Warwick, RI (NOW HIRING)

Samprasoft

Machine Learning Engineer

Smithfield, RI

Sr. Machine Learning Engineer Duration: 12 -24 Months Location: Merrimack, NH/ Smithfield, RI/ Westlake, TX/ Durham, NC/ Covington, KY/ Jersey City, NJ/ Boston, MA Candidate should be local or ...

Indeed

Machine Learning Engineer III

Providence, RI

Comscore, Total Visits, March 2025) Day to Day As a Machine Learning Engineer III, you will be a team lead. You will own one of the team's major workstreams, help drive technical direction for the ...

Indeed

Senior Machine Learning Engineer

Providence, RI

$105K - $145K/yr

Comscore, Total Visits, March 2025) Day to Day As a Senior Machine Learning Engineer on our Sourcing team, you will work on developing and deploying ML and AI solutions in production. You'll be ...

Bespoke Labs

Machine Learning Engineer

Warwick, RI

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Bristol, RI

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Cranston, RI

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

next page

Showing results 1-20

All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Warwick, RI

Machine Learning Engineer information

See Warwick, RI salary details

$30.8K

$125.7K

$188.9K

How much do machine learning engineer jobs pay per year?

As of Jun 21, 2026, the average yearly pay for machine learning engineer in Warwick, RI is $125,710.00, according to ZipRecruiter salary data. Most workers in this role earn between $99,100.00 and $151,300.00 per year, depending on experience, location, and employer.

Is ML full of coding?

Machine Learning Engineers typically do a significant amount of coding, especially in languages like Python or R, to develop algorithms, preprocess data, and build models. Strong programming skills are essential, along with knowledge of frameworks such as TensorFlow or PyTorch, but the role also involves data analysis, model evaluation, and collaboration with teams. Coding is a core component of the job, though some tasks may involve model deployment and optimization that require different skills.

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-paying industries such as finance or technology can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially at large tech companies 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 they develop, implement, and maintain AI systems, requiring specialized skills in programming, data analysis, and model optimization. Roles that involve complex problem-solving, creativity, and human interaction—such as healthcare professionals, educators, skilled tradespeople, and certain managerial positions—are also expected to persist despite AI advancements. These jobs typically require emotional intelligence, adaptability, and domain expertise that AI cannot easily replicate.

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 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 job categories do people searching Machine Learning Engineer jobs in Warwick, RI look for? The top searched job categories for Machine Learning Engineer jobs in Warwick, RI are:
What cities near Warwick, RI are hiring for Machine Learning Engineer jobs? Cities near Warwick, RI with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Warwick, RI as of June 2026, with employment types broken down into 100% Full Time. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $125,710 per year, or $60.4 per hour.
Machine Learning Engineer

Machine Learning Engineer

Samprasoft

Smithfield, RI

Other

Posted 10 days ago

Job description

Sr. Machine Learning Engineer

Duration: 12 -24 Months

Location: Merrimack, NH/ Smithfield, RI/ Westlake, TX/ Durham, NC/ Covington, KY/ Jersey City, NJ/ Boston, MA

Candidate should be local or willing to work onsite on any of the above locations for 5 days/ month

The Expertise And Skills You Bring
  • Bachelor’s or Master’s Degree in a technology related field (e.g. Engineering, Computer Science, etc.)
  • 8+ years of proven experience in implementing Big data solutions in data analytics space
  • 2+ years of experience in developing ML infrastructure and MLOps in the Cloud using AWS Sagemaker
  • Extensive experience working with machine learning models with respect to deployment, inference, tuning, and measurement required
  • Experience in Object Oriented Programming (Java, Scala, Python), SQL, Unix scripting or related programming languages and exposure to some of Python’s ML ecosystem (numpy, panda, sklearn, tensorflow, etc.)
  • Experience with building data pipelines in getting the data required to build and evaluate ML models, using tools like Apache Spark or other distributed data processing frameworks
  • Data movement technologies (ETL/ELT), Messaging/Streaming Technologies (AWS SQS, Kinesis/Kafka), Relational and NoSQL databases (DynamoDB, EKS, Graph database), API and in-memory technologies
  • Strong knowledge of developing highly scalable distributed systems using Open-source technologies
  • Experience with CI/CD tools (e.g., Jenkins or equivalent), version control (Git), orchestration/DAGs tools (AWS Step Functions, Airflow, Luigi, Kubeflow, or equivalent)
  • Solid experience in Agile methodologies (Kanban and SCRUM)
  • Strong technical design and analysis skills
  • Ability to deal with ambiguity and work in fast paced environment
  • Experience supporting critical applications
  • Familiarity with applied data science methods, feature engineering and machine learning algorithms
  • Data wrangling experience with structured, semi-structured and unstructured data
  • Experience building ML infrastructure, with an eye towards software engineering
  • Excellent communication skills, both through written and verbal channels
  • Excellent collaboration skills to work with multiple teams in the organization
  • Ability to understand and adapt to changing business priorities and technology advancements in Big data and Data Science ecosystem

Required Skills : Basic Qualification : Additional Skills : Please do not send junior candidates, Need 10 plus years of experience.

Apply