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Junior Machine Learning Jobs (NOW HIRING)

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Machine Learning Engineer

Seattle, WA · On-site

As a Machine Learning Engineer (MLE) on the AI & ML (Insights) team, you will play a critical role ... Provide situational guidance to junior engineers and contribute to team best practices * Build and ...

Blue Yonder, Inc.

Sr. Machine Learning Engineer

Coppell, TX · On-site

$97K - $133K/yr

Mentor junior engineers and foster a culture of learning and growth within the team. Collaborate ... Machine Learning Engineer, or a related/similar position. Experience therein to include the ...

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How much do junior machine learning jobs pay per hour?

As of Aug 7, 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 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.

What are the key skills and qualifications needed to thrive as a junior machine learning engineer?

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.
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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:
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Junior Machine Learning jobs near you
Infographic showing various Junior Machine Learning job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 24% Part Time, 1% Temporary, and 2% 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.

Machine Learning Engineer III

TeleTracking Technologies, Inc.

Pittsburgh, PA • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 3 days ago

Job description

About us
TeleTracking began with a simple but powerful belief that no one should wait for the care they need. More than a slogan, it's a promise to continually improve healthcare.
TeleTracking builds groundbreaking technology incorporating deep clinical expertise. Our solutions are used in the nation's largest healthcare systems and around the world to positively impact patients, families and communities.
What's your contribution to the TeleTracking story?
When you chose to bring your passion and skills to helping achieve our purpose, you'll be part of a team that understands that there's a human life behind every data point. Your skills, curiosity, and compassion-will help fuel our innovation and achieve the TeleTracking promise of revolutionizing modern healthcare.
About the role
We are seeking a highly skilled and experienced Senior Machine Learning Engineer to join our innovative team at TeleTracking Technologies, focusing on improving patient care. The ideal candidate will have a strong background in developing, deploying, and optimizing machine learning models, as well as expertise in data ingestion and modeling techniques. This role requires a deep understanding of hospital operations, healthcare data, clinical workflows, and regulatory requirements (such as HIPAA or GDPR). The successful candidate will be passionate about leveraging advanced technologies to enhance patient care and operational efficiency.
What you will do
  • Design, develop, and implement machine learning and deep learning models to address hospital-specific challenges such as patient flow optimization, resource allocation, bed management, and predictive analytics for patient outcomes.
  • Build and optimize data ingestion and modeling pipelines as needed
  • Utilize domain driven techniques and design patterns to build and contribute to technical
  • design.
  • Collaborate with cross-functional teams including data scientists, software engineers, clinicians, hospital administrators, and experts in TeleTracking Technologies to identify and develop high-impact machine learning solutions.
  • Work with large-scale healthcare and hospital datasets including structured data (EHRs, hospital operational data), unstructured data (clinical notes, imaging).
  • Ensure data privacy and security, adhering to healthcare regulations such as HIPAA and GDPR, especially when working with sensitive hospital data.
  • Mentor junior engineers and data scientists, providing guidance on machine learning techniques, particularly those relevant to hospitals and healthcare systems.
  • Monitor, troubleshoot, and enhance the performance of deployed models using MLOps best practices, ensuring they operate effectively in hospital environments.
  • Write technical architectural and design documents.

What we look for
  • Proven experience in end-to-end design and deployment of machine learning models from ideation to production in healthcare or similar settings.
  • Strong programming skills and experience with object or component-oriented development software, one or more of: Python or R, with proficiency in ML frameworks, one or more of: TensorFlow, PyTorch, or Scikit-learn.
  • Expertise in NLP, computer vision, or other specialized machine learning techniques applicable to healthcare and hospital environments.
  • Deep knowledge of a scripting or statistical programming language (Python preferred). Ability to efficiently work with very large datasets and deal with non-standard machine learning datasets (class-imbalances, sparse matrices, etc.)
  • Assess model performance; train multiple models; carry out tuning. Run A/B tests on models.
  • Comfortable writing complex SQL queries and developing python packages.
  • Experience with cloud-based management and hosting, one or more of: AWS, Azure, GCS, CloudFormation, Terraform, or Ansible. Interest in developing services as well as the underlying infrastructure
  • Experience with database management system software, one or more of: Oracle, MSSQL, MongoDB, MySQL, DynamoDB, or PostgreSQL.
  • Experience with Version Control Software, one or more of: git, Mercurial, CVS, TFS, or Subversion.
  • Strong understanding and experience executing several software development methodologies and life cycles. Ability to understand and translate business requirements into technical specifications.
  • Experience with agile development practices.
  • Excellent written and oral communication skills. Adept and presenting complex topics, influencing, and executing with timely / actionable follow-through.
  • Strong analytical and problem-solving skills with the ability to convert information into practical training deliverables. Uses rigorous logic and methods to solve difficult problems.
  • Knowledge of clinical workflows and hospital operations, and how technology can enhance efficiency and patient care.
  • Familiarity with healthcare-specific machine learning challenges, such as data imbalance, longitudinal data, and real-time processing in hospital environments.
  • Be an active listener, probe requirements for all projects from relevant stakeholders, stay nimble and willing to produce rapid iterations.

Education
  • Bachelor's degree in computer science, Data Science, Machine Learning, Artificial Intelligence, or a related field; 7 or more years of experience.
  • Master's or PhD in Computer Science, Data Science, Machine Learning, Artificial Intelligence, or a related field; 5 or more years of experience. (preferred)

Applicants must be authorized to work in the U.S. without the need for employment-based visa sponsorship now or in the future.
Benefits
  • Employee Medical/dental/vision premiums paid 100% - family members without coverage Medical 100% - small cost for dependents on dental and vision, which start from day one!
  • Life and AD&D
  • Flexible Spending Accounts: Medical, Dependent Care, and Transportation
  • 401 (k) Retirement Savings
  • Tuition Reimbursement
  • Military Paid Leave (up to 6 months of base salary while on military leave)
  • Paid Time Off
  • Paid parental leave

Disclaimer:
The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job. Reasonable accommodation may be made to enable qualified individuals with disabilities to perform the essential functions. The term "qualified individual with a disability" means an individual with a disability who, with or without reasonable accommodation, can perform the essential functions of the position.
TeleTracking is an Equal Opportunity/Affirmative Action employer. TeleTracking recruits qualified applicants without regard to race, color, religion, gender, age, ethnic or national origin, veteran status, physical or mental disability, genetic information, sexual orientation or preference, gender identity, marital status, or citizenship status.
Recruiting agencies, please do not submit unsolicited referrals for this or any open role. We have a roster of agencies with whom we partner, and we will not pay any fee associated with unsolicited referrals.

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