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Remote Aws Machine Learning Jobs in New Hampshire

Strong foundations in modern machine learning, including deep learning, optimization ... Remote work, medical insurance, flexible time off, retirement savings plans, and modern family ...

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Strong foundations in modern machine learning, including deep learning, optimization ... Remote work, medical insurance, flexible time off, retirement savings plans, and modern family ...

New

Strong foundations in modern machine learning, including deep learning, optimization ... Remote work, medical insurance, flexible time off, retirement savings plans, and modern family ...

New

Strong foundations in modern machine learning, including deep learning, optimization ... Remote work, medical insurance, flexible time off, retirement savings plans, and modern family ...

New

Strong foundations in modern machine learning, including deep learning, optimization ... Remote work, medical insurance, flexible time off, retirement savings plans, and modern family ...

New

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Remote Aws Machine Learning information

What is a remote AWS Machine Learning job?

Remote AWS Machine Learning jobs involve working with Amazon Web Services' suite of machine learning tools and services, such as SageMaker, to build, train, and deploy machine learning models. These positions allow professionals to work from anywhere, collaborating with teams virtually while leveraging AWS infrastructure to solve data-driven problems. Responsibilities often include data preprocessing, model development, and deploying scalable solutions in the cloud. Typical job titles may include Machine Learning Engineer, Data Scientist, or AI Developer, all with a focus on AWS technologies. These roles require strong programming skills, experience with cloud computing, and a background in machine learning or data science.

What are the key skills and qualifications needed to thrive as a remote AWS Machine Learning engineer?

To thrive as a Remote AWS Machine Learning Engineer, you need a strong background in machine learning algorithms, statistical analysis, and proficiency in programming languages such as Python, often supported by a relevant degree or certification. Familiarity with AWS services like SageMaker, Lambda, and EC2, as well as experience using cloud-based ML tools and AWS Certified Machine Learning credentials, is typically required. Excellent problem-solving skills, self-motivation, and clear written communication are valuable soft skills for remote collaboration and project management. These skills ensure effective model development, seamless deployment on cloud infrastructure, and successful remote teamwork in delivering scalable ML solutions.

What are some common challenges faced by remote AWS Machine Learning engineers, and how can they be addressed?

Remote AWS Machine Learning engineers often face challenges related to communication and collaboration, especially when working across different time zones and with cross-functional teams. Ensuring secure access to data and cloud resources is another key concern, given the sensitive nature of many machine learning projects. To overcome these challenges, engineers should leverage AWS collaboration tools, maintain clear documentation, and participate in regular virtual meetings. Additionally, setting up robust security protocols and using AWS Identity and Access Management (IAM) helps safeguard project assets while enabling effective teamwork.

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

AspectRemote Aws Machine LearningRemote Data Scientist
Required CredentialsAWS certifications, machine learning coursesStatistics, data analysis, programming skills
Work EnvironmentCloud platforms, AWS services, remote teamsData analysis, modeling, research in remote settings
Industry UsageTech, finance, healthcare using AWS ML toolsResearch, consulting, analytics across industries

Remote AWS Machine Learning specialists focus on deploying machine learning models using AWS cloud services, requiring AWS certifications and cloud expertise. Remote Data Scientists analyze data, build models, and interpret results, often with a stronger emphasis on statistics and programming. While both roles work remotely and involve data, AWS Machine Learning roles are more cloud and deployment-oriented, whereas Data Scientists focus on data analysis and research.

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

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

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

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

What cities in New Hampshire are hiring for Remote Aws Machine Learning jobs?

Cities in New Hampshire with the most Remote Aws Machine Learning job openings:

Postdoctoral Research Associate

University System of New Hampshire

Durham, NH • On-site, Remote

$65K/yr

Full-time

This job post has expired today. Applications are no longer accepted.


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

47th of 629 rated colleges and universities


Job description

USNH Employees should apply within Workday through the Jobs Hub app

The Center for Coastal and Ocean Mapping at the University of New Hampshire (UNH) seeks an exceptional marine scientist to ll a Postdoctoral Research Associate position. The successful candidate will hold a Ph.D. in marine biology or a closely related eld and will have experience in marine geospatial analytics, remote sensing, machine learning and benthic systems.

This position oers an opportunity to contribute to cutting-edge research, particularly advancing the use of remote sensing datasets and machine learning for constructing predictive models for benthic and pelagic sheries and aquaculture site selection. The role is supported by a grant-funded project and includes opportunities for publishing, presenting, and mentoring. This is a one-year position.

Duties/Responsibilities Research & Analysis (90%)
  • Conduct independent research focused on integrating robust machine learning and statistical approaches with acoustic data to investigate relationships of seaoor and environmental variability.

  • Assist in acquiring ground-truth data for this and related projects

  • Travel as required to present research at national and international conferences

Collaboration and Mentorship (10%)
  • Assist with the preparation of annual progress reports, conference papers and journal articles

  • Provide mentorship to graduate students and sta working on related topics.

RequirementsMinimum Acceptable Education & Experience:
  • Ph.D. in Marine Biology, Ecology, Oceanography or related eld

  • Demonstrated expertise in remote sensing, machine learning and data acquisition

  • Ability to work independently while contributing to collaborative, interdisciplinary research

Required Licenses & Certications:
  • Boating license

  • AAUS Scientic Diving Certication

Knowledge, Skills & Abilities:
  • Strong analytical, problem solving, and research skills to design, integrate and interpret complex datasets

  • Eective communication and collaboration abilities, including writing publications and engaging with interdisciplinary teams, and delivering presentations.

  • Self-management and attention to detail, with the ability to work independently and learn emerging tools and methods.

Preferred Qualications:
  • Experience utilizing bathymetric, remote sensing and optical datasets for machine learning

  • Experience acquiring ground-truth data

  • Familiarity with the Gulf of Maine ecosystem

Applicant Instructions

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

  • Resume/CV

  • Cover Letter

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

$65,000.00/Annually

This is a Fiscal Year position (26 pay periods)

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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