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Remote Machine Learning Jobs in New Hampshire (NOW HIRING)

Trimble, Inc.

Technical Training Professional

Portsmouth, NH · On-site +1

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

... live learning sessions. Essential Skills & Experience: • You possess 2+ years of direct ... Hybrid/Remote options available Travel Requirement: Up to 30% (with onsite training requiring no ...

Q LLC

Software Engineer

Dover, NH · On-site +1

Experience collaborating with offsite/remote teams, with excellent communication skills to ensure smooth project execution. * Strong problem-solving skills and the ability to troubleshoot issues in a ...

NTT DATA Services

Data Engineer - Hybrid On-Site

Merrimack, NH · On-site +1

$102K - $136K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

While many positions offer remote or hybrid work options, these arrangements are subject to change based on client requirements. For employees near an NTT DATA office or client site, in-office ...

All JobsMachine Learning JobsRemote Machine Learning JobsRemote Machine Learning Jobs in New Hampshire

Remote Machine Learning information

See New Hampshire salary details

$24.8K

$41.4K

$85.6K

How much do remote machine learning jobs pay per year?

As of Aug 15, 2026, the average yearly pay for remote machine learning in New Hampshire is $41,413.00, according to ZipRecruiter salary data. Most workers in this role earn between $31,600.00 and $44,700.00 per year, depending on experience, location, and employer.

What is a remote machine learning job?

A remote machine learning job involves working with algorithms, data, and models to develop predictive systems or automate tasks, all while working from a location outside of a traditional office setting. Professionals in this role use techniques from statistics and computer science to analyze data, train machine learning models, and deploy solutions for real-world applications. Remote machine learning jobs can span various industries, including technology, healthcare, finance, and e-commerce. These roles typically require strong programming skills, knowledge of machine learning frameworks, and the ability to communicate findings effectively with team members or stakeholders. Working remotely offers flexibility, but also requires discipline and self-motivation to succeed.

What are some effective strategies for collaborating with team members while working remotely as a machine learning engineer?

Collaboration in a remote Machine Learning role often relies on clear communication through digital tools such as Slack, Zoom, and project management platforms like Jira or Asana. Regular check-ins and stand-up meetings help keep everyone aligned on project goals and timelines. Sharing code and models via version control systems (like Git) and using collaborative notebooks (such as JupyterHub or Google Colab) are also common practices. Building strong documentation habits and proactively seeking feedback can help ensure smooth teamwork and project success, even across different time zones.

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

AspectRemote Machine LearningData Scientist
Required CredentialsBachelor's/Master's in CS, ML certificationsBachelor's/Master's in CS, Statistics, or related field
Work EnvironmentRemote, collaborative teams, tech companiesRemote or on-site, diverse industries, analytics focus
Industry UsageTech, AI startups, researchFinance, healthcare, e-commerce, tech
Search & Comparison IntentOften compared for technical roles in AI/MLBroader data analysis roles, but overlapping skills

Remote Machine Learning specialists focus on developing algorithms and models primarily in tech environments, often requiring advanced programming and ML knowledge. Data Scientists analyze data to extract insights, sometimes utilizing ML techniques. While both roles share skills and credentials, Remote Machine Learning emphasizes model development, whereas Data Scientists focus on data analysis and interpretation.

Can remote machine learning engineers work remotely?

Yes, remote machine learning engineers can work remotely, as many companies offer flexible work arrangements for data science and AI roles. These positions typically require strong programming skills, experience with tools like Python and TensorFlow, and the ability to collaborate virtually using communication platforms. Remote work in this field is common, especially for roles focused on model development, data analysis, and deployment.
More about Remote Machine Learning jobs

What are the most commonly searched types of Machine Learning jobs in New Hampshire?

The most popular types of Machine Learning jobs in New Hampshire are:

What are popular job titles related to Remote Machine Learning jobs in New Hampshire?

For Remote Machine Learning jobs in New Hampshire, the most frequently searched job titles are:

What job categories do people searching Remote Machine Learning jobs in New Hampshire look for?

The top searched job categories for Remote Machine Learning jobs in New Hampshire are:

Remote Machine Learning jobs near you
Infographic showing various Remote Machine Learning job openings in New Hampshire as of August 2026, with employment types broken down into 15% Internship, 43% Full Time, and 42% Contract. Highlights an 100% Remote job distribution, with an average salary of $41,413 per year, or $19.9 per hour.

Postdoctoral Research Associate

University System of New Hampshire

Durham, NH • On-site, Remote

$55K/yr

Full-time

Re-posted 16 days ago

University System Of New Hampshire rating

8.8

Company rating: 8.8 out of 10

Based on 16 frontline employees who took The Breakroom Quiz

46th of 618 rated colleges and universities

Job description

USNH Employees should apply within Workday through the Jobs Hub app

The Global Ecology group at the Earth Systems Research Center, University of New Hampshire (UNH), has an immediate opening for a postdoctoral research associate. The goal of this project is to advance understanding of how ecosystem functioning, productivity, carbon uptake/stock, and resilience respond to climate change, and how these responses are mediated by biodiversity and management across regional to global scales. The successful applicant will integrate ground-based observations (e.g., eddy covariance measurements, forest inventories) with satellite remote sensing data (e.g., spaceborne lidar and/or hyperspectral observations) and apply machine learning and deep learning approaches to address these questions.
This position is funded by NASA. The appointment is for one year initially and may be renewed depending on funding availability and satisfactory performance.

Duties/Responsibilities

  • Conduct novel research to understand how terrestrial ecosystems respond to climate extremes (e.g., drought, heatwaves) and disturbances, and how these responses are mediated by biodiversity and management, using state-of-the-art ground-based and satellite observations as well as machine learning/deep learning methods.

  • Lead manuscript preparation and conference presentations on project findings, with a strong emphasis on publishing high-quality and high-impact papers.

Requirements

Minimum Acceptable Education & Experience:

  • A Ph.D. in areas such as ecology, remote sensing, atmospheric sciences/meteorology, biogeosciences, forestry/natural resources, environmental science, or a related field is required.

Knowledge, Skills & Abilities:

  • Applicants should be enthusiastic, creative, and highly motivated. Ideal candidates should have one or more of the following experiences: mechanistic understanding of ecosystem functioning and processes, satellite remote sensing, processing of large data sets, machine learning/deep learning, Earth system modeling, and synthesis of in-situ observations.

  • Strong communication, writing, and programming skills and publication record are highly desirable.

Applicant Instructions

Applicants should be prepared to upload the following documents when applying online within the Resume/Cover Letter section of your application:

  • Resume/CV

  • Cover Letter

  • Contact Information for 3 Professional References

Applications that are missing any of the required items may not move forward for consideration. Additional uploaded documents not requested in the position announcement will not be reviewed.

Compensation Pay Range:

$55,000

Please be advised that this position is supported by external sponsor funding. As such, continued employment in this role is contingent upon the availability of those external funds. If, for any reason, the sponsor funding is reduced or discontinued, employment may be subject to modification or termination in accordance with applicable policies and procedures.

The University of New Hampshire is an R1 Carnegie classification research institution providing comprehensive, high-quality undergraduate and graduate programs of distinction. UNH is located in Durham on a 188-acre campus, 60 miles north of Boston and 8 miles from the Atlantic coast and is convenient to New Hampshire's lakes and mountains. There is a student enrollment of 13,000 students, with a full-time faculty of over 600, offering 90 undergraduate and more than 70 graduate programs. The University actively promotes a dynamic learning environment in which qualified individuals of differing perspectives, life experiences, and cultural backgrounds pursue academic goals with mutual respect and shared inquiry.

EEO Statement

The University System of New Hampshire is an Equal Opportunity/Equal Access employer. The University System is committed to creating an environment that values and supports diversity and inclusiveness across our campus communities and encourages applications from qualified individuals who will help us achieve this mission. The University System prohibits discrimination on the basis of race, color, religion, sex, age, national origin, sexual orientation, gender identity or expression, disability, genetic information, veteran status, or marital status.

The pay range for this position is listed above. Actual offer will be based on skills, qualifications, experience, and internal equity, in addition to relevant business considerations. More information on benefits can be found here: USNH Employee Benefits | Human Resources

Location:

Durham

Salary Grade:

Faculty 01

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