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Machine Learning Engineer New Grad Jobs in Maine

Northeastern University

Data Scientist

Portland, ME · On-site

$87K - $123K/yr

... engineering. * Train, evaluate, and compare machine learning models under supervision. * Assist ... Strong curiosity and motivation to learn new tools, techniques, and AI methods. * Openness to ...

Simonds International, LLC

Machine Operator

Hampden, ME

$20 - $21/hr

... engineering, and mill flow. Our people are the foundation of our success, with a legacy spanning ... We're committed to continuous improvement, lifelong learning, exceptional quality, and building ...

Simonds International, LLC

Machine Operator

Hampden, ME

$20 - $21/hr

... engineering, and mill flow. Our people are the foundation of our success, with a legacy spanning ... We're committed to continuous improvement, lifelong learning, exceptional quality, and building ...

Burton Mill Solutions

Machine Operator

Hampden, ME · On-site

$20 - $21/hr

... engineering, and mill flow. Our people are the foundation of our success, with a legacy spanning ... We're committed to continuous improvement, lifelong learning, exceptional quality, and building ...

Burton Mill Solutions

Machine Operator

Hampden, ME · On-site

$20 - $21/hr

... engineering, and mill flow. Our people are the foundation of our success, with a legacy spanning ... We're committed to continuous improvement, lifelong learning, exceptional quality, and building ...

General Motors

Staff ML Compiler Engineer

Augusta, ME · On-site

We pioneer new approaches to model export, kernel development, and performance engineering so that ... Experience developing and deploying machine learning models? Compensation: The compensation ...

NinjaOne

$117K - $154K/yr

... pipelines and machine learning models. o Understanding of Generative AI and Deep Learning ... For roles based in New York, the base salary hiring range for this position is $110,000 to $200,000 ...

FirstLight

Carrier Voice Engineer

Brunswick, ME · On-site

$75K - $95K/yr

Apply AI, machine learning, automation, and advanced analytics to improve fraud detection, threat ... FirstLight, headquartered in Albany, New York, provides fiber-optic data, Internet, data center ...

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Machine Learning Engineer New Grad information

What is a Machine Learning Engineer New Grad job?

A Machine Learning Engineer New Grad job is an entry-level role for recent graduates specializing in machine learning and artificial intelligence. It typically involves developing, training, and deploying machine learning models, working with large datasets, and optimizing algorithms for performance. New grads in this role often collaborate with data scientists, software engineers, and product teams to integrate models into applications. Employers look for proficiency in programming (Python, TensorFlow, PyTorch), a strong foundation in ML concepts, and experience with data processing. This role provides an opportunity to gain hands-on industry experience and grow technical skills in real-world applications.

What are the key skills and qualifications needed to thrive in the Machine Learning Engineer New Grad position, and why are they important?

To thrive as a Machine Learning Engineer New Grad, a strong background in computer science, statistics, and mathematics, often supported by a relevant degree, is essential. Familiarity with programming languages like Python or Java, machine learning frameworks (such as TensorFlow or PyTorch), and basic knowledge of data tools and cloud platforms is typically required. Effective problem-solving, eagerness to learn, and clear communication help new grads excel when collaborating on projects and learning from senior team members. These skills and qualities are vital for adapting quickly, contributing to team goals, and building a successful foundation in this fast-evolving technical field.

What are the typical day-to-day tasks of a Machine Learning Engineer New Grad?

As a Machine Learning Engineer New Grad, your daily tasks often include collecting and preprocessing data, developing and testing machine learning models, and analyzing model performance. You may work closely with data scientists and software engineers to integrate models into production systems and address real-world business problems. Participating in team meetings, code reviews, and collaborative projects is common, providing opportunities to learn best practices and receive mentorship. This hands-on, varied workload helps you quickly build technical and collaborative skills early in your career.

What are popular job titles related to Machine Learning Engineer New Grad jobs in Maine? For Machine Learning Engineer New Grad jobs in Maine, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer New Grad jobs in Maine look for? The top searched job categories for Machine Learning Engineer New Grad jobs in Maine are:
What cities in Maine are hiring for Machine Learning Engineer New Grad jobs? Cities in Maine with the most Machine Learning Engineer New Grad job openings:
Machine Learning Engineer New Grad jobs near you
Infographic showing various Machine Learning Engineer New Grad job openings in Maine as of June 2026, with employment types broken down into 89% Full Time, and 11% Part Time. Highlights an 89% In-person, and 11% Remote job distribution.

Data Scientist

Northeastern University

Portland, ME • On-site

$87K - $123K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 4 days ago

Job description

About the Opportunity
JOB SUMMARY
This is a full-time, one-year term appointment with the possibility of renewal. The position is in-person at Northeastern's Roux Institute in Portland, Maine.
The Data Scientist at the AI Solutions Hub (AISH), the delivery arm of Northeastern University's Experiential AI Institute, will support the development and delivery of AI and data science solutions across diverse industries. The role is designed for early-career data scientists who will work under the guidance of senior data scientists, AI engineers, and faculty leads.
The Data Scientist will contribute to data analysis, feature engineering, model development, evaluation, and documentation, while progressively gaining exposure to production systems, client-facing work, and modern AI practices across Predictive AI and Generative AI use cases.
Education & Experience
  • Master's degree (required) or Ph.D. (optional) in Computer Science, Engineering, Applied Mathematics, Statistics, or a closely related field.
  • 0-2 years of industry, research, or applied project experience in data science or machine learning.
  • Experience gained through internships, co-ops, academic research, or applied capstone projects is acceptable.
  • Industry experience is preferred.

Knowledge, Skills, and Abilities
Technical and Analytical Foundations
  • Solid understanding of statistical methods, regression, hypothesis testing, and basic experimental design.
  • Hands-on experience with classical machine learning methods such as linear/logistic regression, decision trees, and gradient boosting.
  • Familiarity with deep learning concepts and modern architectures (e.g., convolutional neural networks or transformers); deep specialization is not required.
  • Exposure to Generative AI concepts and large language models (LLMs) is a plus.
  • Proficiency in Python for data analysis and model development (NumPy, pandas, scikit-learn).
  • Working knowledge of SQL and relational databases.
  • Familiarity with at least one ML or deep learning framework (e.g., PyTorch, TensorFlow, HuggingFace).
Model Development and Delivery Support
  • Perform data cleaning, exploratory data analysis (EDA), and feature engineering.
  • Train, evaluate, and compare machine learning models under supervision.
  • Assist with model validation, performance monitoring, and documentation.
  • Contribute to ML pipelines and collaborate with ML engineers on deployment-related tasks.
Collaboration and Communication
  • Ability to clearly communicate analytical findings to technical and non-technical audiences with guidance.
  • Collaborate effectively with cross-functional teams including data scientists, engineers, project managers, and faculty experts.
  • Willingness to participate in client meetings in a supporting role.
Preferred Experience
  • Exposure to NLP, computer vision, or speech processing through coursework or academic/industry projects.
  • Familiarity with cloud platforms (AWS, Azure, or GCP).
  • Understanding of software development best practices such as version control (Git) and Agile workflows.

Values & Professional Attributes
Ethical and Responsible AI
  • Awareness of ethical AI principles including fairness, transparency, and responsible model use.
  • Willingness to follow established governance, documentation, and review practices.
Learning and Growth Mindset
  • Strong curiosity and motivation to learn new tools, techniques, and AI methods.
  • Openness to feedback and mentorship.
Execution and Ownership
  • Ability to manage assigned tasks, meet deadlines, and maintain high-quality work.
  • Proactive attitude and willingness to take increasing responsibility over time.

Position Type
Research
Additional Information
Northeastern University considers factors such as candidate work experience, education and skills when extending an offer.
Northeastern has a comprehensive benefits package for benefit eligible employees. This includes medical, vision, dental, paid time off, tuition assistance, wellness & life, retirement- as well as commuting & transportation. Visit https://hr.northeastern.edu/benefits/ for more information.
All qualified applicants are encouraged to apply and will receive consideration for employment without regard to race, religion, color, national origin, age, sex, sexual orientation, disability status, or any other characteristic protected by applicable law.
Compensation Grade/Pay Type:
111S
Expected Hiring Range:
$87,785.00 - $123,998.75
With the pay range(s) shown above, the starting salary will depend on several factors, which may include your education, experience, location, knowledge and expertise, and skills as well as a pay comparison to similarly-situated employees already in the role. Salary ranges are reviewed regularly and are subject to change.

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