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Junior Machine Learning Jobs (NOW HIRING)

Rockstar

Jr AI Engineer

Position Summary Our client is seeking a Jr. AI Engineer/Jr. Machine Learning Engineer to support the development, testing, and improvement of AI-powered features across their data intelligence ...

Hive

Machine Learning Manager

San Francisco, CA

$180K - $250K/yr

... junior engineers through their journey to become better. Responsibilities * Interface closely with product management, engineering, devops, labeling, and sales teams to build roadmap in supporting ...

Hive

Machine Learning Manager

Seattle, WA · On-site

$180K - $250K/yr

... junior engineers through their journey to become better. Responsibilities * Interface closely with product management, engineering, devops, labeling, and sales teams to build roadmap in supporting ...

Hive

Machine Learning Manager

Seattle, WA

$180K - $250K/yr

... junior engineers through their journey to become better. Responsibilities * Interface closely with product management, engineering, devops, labeling, and sales teams to build roadmap in supporting ...

Hive

Machine Learning Manager

San Francisco, CA · On-site

$180K - $250K/yr

... junior engineers through their journey to become better. Responsibilities * Interface closely with product management, engineering, devops, labeling, and sales teams to build roadmap in supporting ...

SynergisticIT

Junior Machine Engineer

Buffalo Grove, IL · On-site

Math's is quite an important skill in the arsenal of a Machine Learning engineer. Computer Science Fundamentals and Programming. NLP and Text Mining Required. Pandas Data Analysis Required Experience ...

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Junior Machine Learning information

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How much do junior machine learning jobs pay per hour?

As of Jun 27, 2026, the average hourly pay for junior machine learning in the United States is $26.96, according to ZipRecruiter salary data. Most workers in this role earn between $16.35 and $33.17 per hour, depending on experience, location, and employer.

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

AspectJunior Machine LearningData Scientist
Required CredentialsBachelor's in CS, Data Science, or related field; some experience with ML toolsBachelor's or Master's in CS, Statistics, or related; strong programming and statistical skills
Work EnvironmentEntry-level projects, supervised tasks, team collaborationAdvanced analysis, model development, cross-functional teams
Industry UsageCommon in tech companies, startups, research labsWidespread across industries like finance, healthcare, tech

Junior Machine Learning roles focus on foundational ML tasks and learning on the job, while Data Scientists handle complex data analysis, model building, and strategic insights. The roles differ mainly in experience level and scope of responsibilities, but both require strong technical skills and familiarity with data tools.

What does a Junior Machine Learning Engineer do?

A Junior Machine Learning Engineer assists in the development and implementation of machine learning models and algorithms under the supervision of more experienced engineers. They typically help with data collection, cleaning, feature engineering, model training, and evaluation. Junior engineers may also write code, test prototypes, and contribute to improving model performance while learning best practices in the field. Their role often involves collaborating with data scientists and software engineers to integrate machine learning solutions into products or services.

What engineers make $500,000?

Senior engineers in fields like software, data engineering, or specialized roles such as machine learning engineers can earn $500,000 or more annually, especially with experience, advanced skills, and in high-demand industries. Compensation often includes base salary, bonuses, and stock options, particularly at large tech companies or startups with significant funding.

What types of projects and tasks can a Junior Machine Learning professional typically expect to work on in their first year?

As a Junior Machine Learning professional, you’ll often support senior data scientists and engineers by preparing data, implementing basic algorithms, and assisting with model evaluation. Your daily tasks may include data cleaning, feature engineering, running experiments, and writing code to automate data pipelines. You might also help document processes and present your findings to team members. While the work is often collaborative, you’ll have opportunities to take ownership of smaller projects and progressively contribute to larger initiatives as you gain experience.

Can I get into AI with no experience?

Junior Machine Learning roles typically require some foundational knowledge of programming, mathematics, and data analysis. While prior experience is often preferred, beginners can enter the field by learning relevant skills through online courses, tutorials, and projects, and by gaining familiarity with tools like Python and machine learning frameworks. Building a portfolio and obtaining certifications can also improve chances of entry-level employment.

Which 3 jobs will survive AI?

Junior Machine Learning roles are likely to persist as they require specialized knowledge, critical thinking, and domain expertise that AI cannot fully replicate. Jobs involving complex problem-solving, creativity, and human interaction, such as data scientists, AI ethics specialists, and AI system trainers, are also expected to remain in demand. Continuous learning and adapting to new tools will be essential for these roles to stay relevant.

What is a $900,000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers or AI research directors, often requiring advanced skills in deep learning, data science, and experience with tools like TensorFlow or PyTorch. These positions usually involve leadership responsibilities, extensive expertise, and may include stock options or bonuses as part of compensation packages.

What are the key skills and qualifications needed to thrive as a Junior Machine Learning Engineer, and why are they important?

To thrive as a Junior Machine Learning Engineer, you need a solid understanding of programming (especially Python), basic statistics, linear algebra, and familiarity with machine learning concepts, typically supported by a relevant degree or coursework. Proficiency in tools and frameworks like scikit-learn, TensorFlow, PyTorch, and version control systems such as Git is often expected. Strong problem-solving abilities, curiosity, and effective communication are crucial soft skills for collaborating with teams and explaining technical concepts. These skills and qualities are important because they enable you to contribute effectively to building, testing, and improving machine learning models in real-world applications.
More about Junior Machine Learning jobs
What cities are hiring for Junior Machine Learning jobs? Cities with the most Junior Machine Learning job openings:
What are the most commonly searched types of Machine Learning jobs? The most popular types of Machine Learning jobs are:
What states have the most Junior Machine Learning jobs? States with the most job openings for Junior Machine Learning jobs include:
What job categories do people searching Junior Machine Learning jobs look for? The top searched job categories for Junior Machine Learning jobs are:
Junior Machine Learning jobs near you
Infographic showing various Junior Machine Learning job openings in the United States as of June 2026, with employment types broken down into 2% As Needed, 40% Full Time, 57% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $56,068 per year, or $27 per hour.
Junior Machine Learning Engineer

Junior Machine Learning Engineer

ENSCO, Inc.

Melbourne, FL

Other

Posted 6 days ago

Job description

ENSCO, Inc. is seeking a Junior Machine Learning Engineer with direct experience and applications with using Machine Learning (ML) and Deep Learning (DL) models, frameworks, architectures, pipelines, and advanced data analytics, to address difficult problem sets.  Work closely with other senior scientist to understand problem sets, physical data feature sets and parameters.  The successful candidate must have demonstrated understanding of signal processing, data fusion, feature extraction, and be able to apply it towards ML and DL solutions.  Assess algorithm performance of features by building datasets and designing and executing well-controlled experiments.
ENSCO's Mission Systems Group (MSG) provides innovative customized products and services vital to national safety and security.  A primary focus area is the development of advanced algorithm development and integration for multipurpose data sets.
 

Qualifications Required:
        Bachelors degree in Machine Learning, Data Science, Mathematics, or equivalent in a related discipline.  Direct relevant military experience will also be considered.
        Minimum of 2 years related industry experience in machine learning, data science, and analytics.
        Proven track record of successful data science and algorithm implementation.
        A self-starter with excellent oral and written communication skills.
        Experience navigating and programming within the Linux environment.
        Experience working with structured and unstructured databases.
        Advanced proficiency with data science languages (e.g. Python, Matlab,)
        Demonstrated experience with Deep Learning frameworks (e.g. PyTorch, TensorFlow/Keras, scikit-learn, MXNet).
        Experience working with large data sets and ability to extract relevant information from data sets.
        The ability to obtain and maintain a US security clearance is required for this position, for which you must be a U.S. Citizen
 

Qualifications Desired:
        Masters or PhD degree in Machine Learning, Data Science, or Mathematics, or equivalent.
        Experience with ML/DL algorithms extracting signal from noise.
        Past experience being able to develop solutions using disparate data sets through ML techniques.
        DevOps experience involving CI/CD pipelines to build and deploy.
        Experience working with container orchestration technologies (e.g. Docker/Kubernetes).
        An Active TS/SCI clearance.
 

Work Location Type: Hybrid
Required Certifications: None
U.S. Citizenship Required: Yes
Security Clearance Required: Ability to obtain
Employment Type: Regular Full-time
Background Check Type:  7 Year Pre-Employment
Drug Screen Required: None
Position Contingent Upon Contract Award: Yes

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