ZipRecruiter

Log In

2

Entry Level Machine Learning Jobs in Maine (NOW HIRING)

Aerotek

Machine Operator

Kennebunk, ME

$17.75 - $21.25/hr

Exposure to basic preventive maintenance tasks on machinery, even at an entry level. * Mechanical ... learning and internal opportunities. Why Work Here? You will join a family-run operation that ...

All JobsMachine Learning JobsEntry Level Machine Learning JobsEntry Level Machine Learning Jobs in Maine

Entry Level Machine Learning information

See Maine salary details

$11

$16

$20

How much do entry level machine learning jobs pay per hour?

As of Aug 12, 2026, the average hourly pay for entry level machine learning in Maine is $16.91, according to ZipRecruiter salary data. Most workers in this role earn between $15.14 and $18.37 per hour, depending on experience, location, and employer.

What types of projects can an entry level machine learning professional expect to work on in their first year?

As an entry-level machine learning professional, you’ll typically start by supporting more senior data scientists and engineers with tasks such as data cleaning, exploratory data analysis, and building baseline models. You may work on pilot projects like developing recommendation systems, automating simple classification tasks, or contributing to model evaluation and performance tuning. Collaboration with cross-functional teams—including software engineers, product managers, and domain experts—is common, providing valuable exposure to real-world business problems and laying a foundation for more complex responsibilities as you gain experience.

How to get into entry level machine learning with no experience?

Entry level machine learning roles typically require foundational knowledge in programming, statistics, and data analysis. Gaining skills through online courses, practicing with projects, and learning tools like Python, TensorFlow, or scikit-learn can help build a portfolio; internships or entry-level positions can provide practical experience.

What are the key skills and qualifications needed to thrive as an entry level machine learning engineer, and why are they important?

To thrive as an Entry Level Machine Learning Engineer, you need a solid background in mathematics, statistics, and programming (especially in Python), typically supported by a degree in computer science or a related field. Familiarity with machine learning frameworks like TensorFlow or PyTorch, version control systems like Git, and data analysis libraries is commonly required. Strong problem-solving abilities, curiosity, and effective communication skills help differentiate candidates in collaborative and fast-evolving environments. These skills and qualifications are essential for building, testing, and improving machine learning models that drive innovation and business value.

What is the difference between Entry Level Machine Learning vs Data Analyst?

AspectEntry Level Machine LearningData Analyst
Required CredentialsBachelor's in CS, Math, or related; some knowledge of programming and statisticsBachelor's in Statistics, Math, or related; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentTech companies, startups, research labs; focus on developing models and algorithmsBusiness, finance, marketing; focus on interpreting data and generating reports
Employer & Industry UsageTech, e-commerce, healthcare; roles involve building predictive modelsRetail, finance, consulting; roles involve analyzing data trends and insights

Entry Level Machine Learning roles focus on developing algorithms and models using programming and statistical skills, often in tech-driven environments. Data Analysts interpret and visualize data to support business decisions, typically using tools like Excel and SQL. While both roles require analytical skills, Machine Learning positions emphasize coding and model development, whereas Data Analysts focus on data interpretation and reporting.

What are entry level machine learning jobs?

Entry-level machine learning jobs focus on creating and using software for the development of artificial intelligence (AI). In this role, you may help program computer software, engineer mechanical solutions, help develop learning objectives, and use analytics to determine whether or not the technology created is meeting development goals. Many entry-level machine learning jobs focus on particular parts of the industry. For example, some companies focus on surveillance and intelligence, while others are creating technology for self-driving vehicles. Employers often use this position as a type of extended learning period to help you develop your skills before you start taking responsibility for major projects.

More about Entry Level Machine Learning jobs
What are the most commonly searched types of Machine Learning jobs in Maine? The most popular types of Machine Learning jobs in Maine are:
What are popular job titles related to Entry Level Machine Learning jobs in Maine? For Entry Level Machine Learning jobs in Maine, the most frequently searched job titles are:
What job categories do people searching Entry Level Machine Learning jobs in Maine look for? The top searched job categories for Entry Level Machine Learning jobs in Maine are:
Entry Level Machine Learning jobs near you
Infographic showing various Entry Level Machine Learning job openings in Maine as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 22% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $35,171 per year, or $16.9 per hour.

Jr. Data Scientist 00021

West Coast Consulting

Westbrook, ME • On-site

$45 - $48/hr

Full-time

Medical, Life

Re-posted 4 days ago

Job description

Job Description Hybrid -Westbrook, ME Job Description: The Machine Intelligence team in R&D is looking for an entry-level Data Scientist to develop machine learning solutions for the hematology analyzers. In this role, you will work on classification and clustering problems on tabular data, with solutions deployed on edge hardware in our analyzer platforms. You will work under the supervision of a senior data scientist who will guide your technical development and project execution.

We are looking for a curious, adaptable team player eager to build foundational skills in applied machine learning. What you can expect: Develop classification and clustering models on tabular data to support hematology analyzer capabilities Contribute to model development, evaluation, and iteration under the guidance of a senior data scientist Partner with senior team members to understand requirements, explore data, and validate model performance Document your work clearly so it can be reviewed, reproduced, and built upon by the team Deploy your solutions to edge hardware What you need to succeed: 0-2 years of experience applying machine learning to real-world problems (internships, research, and coursework projects count) Strong working knowledge of Python and common data science libraries (pandas, scikit-learn, NumPy) Solid foundation in statistics, machine learning, and algorithms Demonstrated understanding of classification and clustering methods for tabular data, including when to apply which approach and how to evaluate results Curiosity about the data and the underlying generating processes - a habit of asking "why" before reaching for a model A growth mindset and willingness to learn from more senior team members Ability to communicate analyses and results clearly to your immediate team Bachelor's degree in a quantitative field (statistics, computer science, math, engineering, or related); advanced degree a plus Nice to have: Exposure to deploying ML models on resource-constrained or edge hardware Familiarity with model optimization techniques (quantization, ONNX, TFLite) Experience with version control (Git) and collaborative software development practices Experience modeling data for medical, diagnostic or life sciences applications

Apply