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Junior Machine Learning Engineer Jobs in Pittsburgh, PA

Varsity Tutors

Machine Learning Tutor

Pittsburgh, PA · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Skild AI

Robotics Software Engineer

Pittsburgh, PA · On-site

$100K - $300K/yr

We believe massive scale through data-driven machine learning is the key to unlocking these ... Position Overview We are seeking a versatile Robotics Software Engineer to develop and implement ...

Deloitte

Senior AI Engineer - SFL Scientific

Pittsburgh, PA · On-site

$101K - $139K/yr

Work with clients to design, develop, and deploy new architectures to support machine learning ... Mentor, motivate, and coach junior members on technical best practices and inspire professional ...

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All JobsMachine Learning Engineer JobsJunior Machine Learning Engineer JobsJunior Machine Learning Engineer Jobs in Pittsburgh, PA

Junior Machine Learning Engineer information

See Pittsburgh, PA salary details

$32.5K

$69.7K

$106.3K

How much do junior machine learning engineer jobs pay per year?

As of Sep 5, 2026, the average yearly pay for junior machine learning engineer in Pittsburgh, PA is $69,704.00, according to ZipRecruiter salary data. Most workers in this role earn between $47,100.00 and $77,700.00 per year, depending on experience, location, and employer.

What does a junior machine learning engineer do?

As a junior machine learning engineer, you work in AI, performing research with algorithms and data modeling techniques. Machine learning involves using large collections of data to create systems that are capable of making predictions, and in this field, your duties and responsibilities revolve around using advanced mathematics to design applications for use in everything from stock trading to sports betting. Some machine learning efforts involve images, and this branch of the field is known as computer vision, while other techniques which focus on text are called natural language processing (NLP). Given these divisions, titles in machine learning include computer vision engineer, NLP scientist, or simply research scientist.

What kinds of projects and responsibilities can a junior machine learning engineer expect in their first year on the job?

As a Junior Machine Learning Engineer, you’ll typically work on tasks such as data preprocessing, building and testing simple models, and supporting more senior engineers in deploying machine learning solutions. Your responsibilities may also include cleaning datasets, implementing basic algorithms, and running experiments to evaluate model performance. You’ll often collaborate closely with data scientists, software engineers, and product teams to understand project goals and learn best practices. The role provides excellent opportunities to develop your technical skills, gain exposure to various stages of the ML pipeline, and gradually take on more complex projects as you grow.

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

To succeed as a Junior Machine Learning Engineer, you need a solid grasp of programming (especially Python), foundational knowledge of algorithms and statistics, and a relevant degree in computer science, mathematics, or a related field. Familiarity with machine learning frameworks such as TensorFlow or PyTorch and tools like scikit-learn, as well as experience with version control systems like Git, are typically required. Strong problem-solving abilities, attention to detail, and a willingness to learn from feedback are valuable soft skills that help you adapt and grow in the field. These skills ensure you can effectively develop, test, and improve machine learning models while collaborating with more experienced engineers and contributing to team projects.

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

AspectJunior Machine Learning EngineerData Scientist
Required CredentialsBachelor's in CS, Data Science, or related; some experience with ML frameworksBachelor's or higher in CS, Statistics, or related; often advanced certifications
Work EnvironmentDeveloping and deploying ML models, coding, testingData analysis, statistical modeling, interpreting data insights
Employer & Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, tech, consulting
Search & Comparison IntentYesYes

While both roles involve working with data and machine learning, Junior Machine Learning Engineers focus on building and deploying models, often with coding and engineering skills. Data Scientists analyze data, create statistical models, and interpret insights. The roles overlap but differ mainly in their core responsibilities and skill emphasis.

How much do junior machine learning engineers make?

Junior machine learning engineers typically earn between $70,000 and $100,000 annually, depending on location, education, and industry. Entry-level roles often require knowledge of programming languages like Python and familiarity with machine learning frameworks such as TensorFlow or PyTorch.
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Junior Machine Learning Engineer jobs near you
Infographic showing various Junior Machine Learning Engineer job openings in Pittsburgh, PA as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 23% Part Time, and 1% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $69,704 per year, or $33.5 per hour.

Senior / Staff Machine Learning Infrastructure Engineer

Waabi

Pittsburgh, PA • On-site, Remote

$157K - $234K/yr

Full-time

Medical, Dental, Vision, PTO

Re-posted 25 days ago

Job description

Waabi, founded by AI visionary Raquel Urtasun, is the leader in Physical AI. With a world-class team, we're unlocking the next era of autonomous transportation with technology that's powering commercial autonomous trucks and robotaxis. Waabi is backed by and partners with world leaders in AI, automotive, logistics, and deep tech.
 
With offices in Toronto, San Francisco, Dallas, and Pittsburgh, Waabi is growing quickly and looking for diverse, innovative and collaborative candidates who want to impact the world in a positive way. To learn more visit: www.waabi.ai

You will..
- Design, develop, and implement the machine learning platform for the continuous deployment and integration of machine learning models.
- Collaborate with data scientists and engineers to understand model requirements and optimize pipeline processes.
- Automate the training, testing and deployment processes for machine learning models.
- Continuously monitor and maintain model pipelines, ensuring optimal performance, accuracy and reliability.
- Optimize machine learning pipelines for scalability, efficiency and cost-effectiveness.
- Ensure compliance with security and data privacy standards in all MLOps activities.
 
Qualifications:
- 3-5 years of experience supporting machine learning training platforms.
- Bachelor's degree in Computer Science, Data Science or a related field.
- Strong understanding of machine learning principles and model lifecycle management.
- Proficiency in programming languages such as Python, with hands-on experience in machine learning frameworks like TensorFlow or PyTorch.
- Experience with cloud platforms like AWS, Azure, or Google Cloud and their respective machine learning services.
- Experience managing technology such as JupyterHub and Kubeflow.
- Familiarity with containerization and orchestration tools such as Kubernetes and Docker.
- Strong problem-solving skills and ability to troubleshoot complex issues.
- Experience with monitoring tools and practices for model performance in production.
- Ability to work collaboratively in cross-functional teams.
 
Bonus/nice to have: 
- Experience with infrastructure-as-code (IaC) tools such as Terraform or Crossplane.
- Knowledge of big data technologies like Apache Spark or Hadoop.
- Familiarity with data engineering practices and tools.
- Experience with A/B testing and model validation in production environments.
- Relevant MLOps certifications (e.g., AWS Certified Machine Learning - Specialty, DataRobot MLOps Certification) are a plus.
The US yearly salary range for this role is: $157,000 - $234,000 USD in addition to competitive perks & benefits. Waabi (US) Inc.'s yearly salary ranges are determined based on several factors in accordance with the Company's compensation practices. The salary base range is reflective of the minimum and maximum target for new hire salaries for the position across all US locations.  Note: The Company provides additional compensation for employees in this role, including equity incentive awards and an annual performance bonus.

Perks/Benefits:
  • Competitive compensation and equity awards.
  • Health and Wellness benefits encompassing Medical, Dental and Vision coverage (for full-time employees only).
  • Unlimited Vacation.
  • Flexible hours and Work from Home support.
  • Daily drinks, snacks and catered meals (when in office).
  • Regularly scheduled team building activities and social events both on-site, off-site & virtually.
  • As we grow, this list continues to evolve! 
 
Waabi is a technology start-up building technologies to transform the way the world moves. Join our talented team to be a part of the future and to make an impact!
 
Waabi is an equal opportunity employer. We celebrate diversity and are committed to creating a supportive, inclusive, and accessible workplace for all our employees. We seek applicants of all backgrounds and identities, across race, color, ethnicity, national origin or ancestry, age, citizenship, religion, sex, sexual orientation, gender identity or expression, military or veteran status, marital status, pregnancy or parental status, caregiver status, disability, or any other characteristic protected by law. We make workplace accommodations for qualified individuals with disabilities as required by applicable law. If reasonable accommodation is needed to participate in the job application or interview process please let our recruiting team know.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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