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Machine Learning Engineer Jobs in Pittsburgh, PA

Senior Machine Learning Engineer Pittsburgh, Pennsylvania, United States Company Description Govini transforms Defense Acquisition from an outdated manual process to a software-driven strategic ...

Senior Machine Learning Engineer

Pittsburgh, PA · On-site

$118K - $156K/yr

... engineers Qualifications * U.S. Citizenship is required * Advanced degree, or bachelor's with at least 3 years of experience, in Data Science, Machine Learning or a related field Required Skills:

Senior Machine Learning Engineer

Pittsburgh, PA · On-site

$118K - $156K/yr

... engineers Qualifications * U.S. Citizenship is required * Advanced degree, or bachelor's with at least 3 years of experience, in Data Science, Machine Learning or a related field Required Skills:

... engineers Qualifications * U.S. Citizenship is required * Advanced degree, or bachelor's with at least 3 years of experience, in Data Science, Machine Learning or a related field Required Skills:

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Machine Learning Engineer information

See Pittsburgh, PA salary details

$30.6K

$125K

$187.9K

How much do machine learning engineer jobs pay per year?

As of Jun 10, 2026, the average yearly pay for machine learning engineer in Pittsburgh, PA is $125,012.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $150,500.00 per year, depending on experience, location, and employer.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

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

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

What Does a Machine Learning Engineer Do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What are some common challenges faced by Machine Learning Engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

What jobs make $3,000 a month without a degree?

A Machine Learning Engineer typically requires a degree, but roles such as data annotator, technical support specialist, or freelance programmer can sometimes earn around $3,000 monthly without a formal degree, especially with relevant skills and experience. These jobs often involve self-taught skills, online certifications, or on-the-job training and may require proficiency in tools like Python or cloud platforms.
What are the most commonly searched types of Machine Learning Engineer jobs in Pittsburgh, PA? The most popular types of Machine Learning Engineer jobs in Pittsburgh, PA are:
What are popular job titles related to Machine Learning Engineer jobs in Pittsburgh, PA? For Machine Learning Engineer jobs in Pittsburgh, PA, the most frequently searched job titles are:
What cities near Pittsburgh, PA are hiring for Machine Learning Engineer jobs? Cities near Pittsburgh, PA with the most Machine Learning Engineer job openings:
Infographic showing various Machine Learning Engineer job openings in Pittsburgh, PA as of June 2026, with employment types broken down into 100% Full Time. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $125,012 per year, or $60.1 per hour.

Machine Learning Engineer - Autonomy Lab

Carnegie Mellon University

Pittsburgh, PA

$95K - $126K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 19 days ago


Carnegie Mellon University rating

8.6

Company rating: 8.6 out of 10

Based on 24 frontline employees who took The Breakroom Quiz

51st of 535 rated colleges and universities


Job description

What We Do

At the SEI AI Division, we conduct research in applied artificial intelligence and the engineering questions related to the practical design and implementation of Artificial Intelligence (AI) technologies and systems. We currently lead a community-wide movement to mature the discipline of AI Engineering for Defense and National Security.

As our government customers adopt AI and machine learning (ML) to provide leap-ahead mission capabilities, we:

  • build real-world, mission-scale AI capabilities through solving practical engineering problems.

  • discover and define the processes, practices, and tools to support operationalizing AI for robust, secure, scalable, and human-centered mission capabilities.

  • prepare our customers to be ready for the unique challenges of adopting, deploying, using, andmaintainingAI capabilities.

  • identifyand investigate emerging AI and AI-adjacent technologies that are rapidly transforming the technology landscape.

Are you creative, curious, and collaborative? Do you enjoy doing meaningful and complex work? Are you interested in making a difference by bringing innovation to government organizations and beyond? Apply to join our team today!

Position Summary:

As a machine learning engineer in the AI for Autonomy Lab, you will identify, shape, apply, conduct, and lead engineering research that matches critical U.S. government needs. The AI for Autonomy Lab researches and demonstrates the application of AI-related technologies for improving the performance of autonomy systems.

Duties:

  • Solution Development: You’llwork with and lead interdisciplinary teams to turn research results into prototype operational capabilities for government customers and stakeholders.

  • Hands-on Prototyping: You’llconduct and lead novel prototyping in applied artificial intelligence with a focus on machine learning in autonomy and uncrewed systems (multi-domain).

  • Strategy: ** ** You’llwork with AI Division leaders and colleagues to plan, develop, and carry out an overall research and engineering strategy, and to influence the national research and engineering agendaregardingfuture technology.

  • Collaboration:  You'llactivelyparticipateon teams of software developers, researchers, designers, and technical leads.You'llbuild relationships and collaborate with researchers, government customers, and other stakeholders to understand challenges, needs,possible solutions, and research and engineering directions.

  • Mentoring: You'llcontribute to improving the overall technical capabilities of the team by mentoring and teaching others,participatingin design (software and otherwise) sessions, and sharing insights and wisdom across the SEIAIDivision.

Requirements:

  • BS in Computer Science or related discipline with eight (8) years of experience; MS in the same fields with five (5) years of experience; PhD in Computer Science with two (2) years of experience.

  • You must be able and willing to work onsite at an SEI office in Pittsburgh, PA or Arlington, VA 5 days per week.

  • Flexible to travel to other SEI offices, sponsor sites, conferences, and offsite meetings on occasion. Moderate (25%) travel outside of your home location.

  • Youwill be subject to a background investigation and must be eligible to obtain andmaintaina Department ofWarsecurity clearance.

Knowledge, Skills, and Abilities:

  • Deep Technical Knowledge:  You have performed extensive research or engineering activities in applied machine learning and artificial intelligence. You have worked with tools, techniques, algorithms, software, and programming languages for deep learning, reinforcement learning, statistics, sensors and sensor fusion, planning, computer vision, or related areas. In addition, you havedemonstratedapplying systems engineering principles and collaborated across multi-disciplinary project teams. You have supported multiple phases of the engineering lifecycle and understand the requirements for successful deployment and operation of complex systems.

  • Machine Learning: You have profound understanding of machine learning principles and have experience in applying machine learning techniques to real-world problems,showcasinga track recordof successful implementations. You have designed and implemented complex machine learning functions and architectures tailored to specific autonomous systems. You are familiar with simulation environments and their role in training and testing machine learning models.

  • Robotics & Autonomy: You have a strong understanding of robotics principles and design techniques for air, sea, or land-based vehicles. You have experience applying machine learning within these domains and understand the related implications and challenges. Your experience includes areas such as sensor fusion, navigation, object search/tracking, collision avoidance, multi-agent collaboration, and human-machine teaming.

  • Test & Evaluation: You have designed and conducted test and evaluation activities for ML components to assess operational fit and readiness. You have experience working with model experimentation software, such asMLFlowor Weights & Biases for rigorous model development and selection.

  • Applied Full-Stack Implementation: You have strong development experience and can design and implement software and systems resources for packaging and managing requirements for AIandML prototypes. Youfrequentlyuse tools like Docker to manage software resources and pipeline orchestration. You may have experience building applications in cloud platforms (Azure, AWS, Google Cloud Platform).

  • Communication and Collaboration:  You have strong written and verbal communication skills and can interact collaboratively and diplomatically with customers and colleagues. You grasp the big picture, direction, and goals of an effort while focusing great attention to detail. You can present complex ideas to people who may not have a deep understanding of the subject area.

  • Dedication: ** ** You can meet deadlines while multi-tasking–sometimes under pressure and with shifting priorities.

  • Creativity and Innovation:  You are creative and curious, and you are inspired by the prospect of collaborating with premier members of the technical staff and other visionaries at Carnegie Mellon and other universities and organizations. You quickly learn new procedures, techniques, and approaches. You are forward-looking and can connect research and engineering with practical challenges.

  • Knowledge and Learning:  Youpossessbroad technical interests along with a deep knowledge of a particular field such as machine learning, autonomy and adaptive systems, or data analytics.

Preferred Experience :

  • Thought Leadership and Publications: You havea track recordof synthesizing lessons learned from research or engineering activities for publication. You have a reputation for the highest level of research and engineering integrity. You havedemonstratedcontributions and have published research, code (e.g., models, data, software applications), or technical perspectives.

  • Familiarity with Emerging Trends and Opportunities: You are familiar with technical challenges and emerging trends in computing and information science, and you are aware of opportunities in industry and government.

  • Technical Leadership: You have led technical projects and have experience collaborating across research teams and mentoring other researchers.

  • Proposals:  You have formulated and delivered successful research and engineering proposals to funding agencies and led the resulting projects.

  • Government Projects:  You have worked or are familiar with Navy, Marine, Air Force, Army, Space Force, DARPA, IARPA, Service Labs, or other government research sponsors.

Joining the CMU team opens the door to an array of exceptional benefits.

Benefits eligible (https://www.cmu.edu/hr/benefits/eligibility/index.html) employees enjoy a wide array of benefits including comprehensive medical, prescription, dental, and vision insurance (https://www.cmu.edu/hr/benefits/health-welfare/index.html) as well as a generous retirement savings program (https://www.cmu.edu/hr/benefits/retirement-savings/index.html) with employer contributions. Unlock your potential with tuition benefits (https://www.cmu.edu/hr/benefits/tuition/index.html) , take well-deserved breaks with ample paid time off (https://www.cmu.edu/hr/benefits/time-away/pto.html) and observed holidays (https://www.cmu.edu/hr/benefits/time-away/holidays.html) , and rest easy with life and accidental death and disability insurance.

Additional perks include a free Pittsburgh Regional Transit bus pass, access to our Family Concierge Team (https://www.cmu.edu/hr/work-life/support/family-child-care-resources/index.html) to help navigate childcare needs, fitness center access (https://athletics.cmu.edu/recreation/facilities) , and much more!

For a comprehensive overview of the benefits available, explore our Benefits page (https://www.cmu.edu/hr/benefits/index.html) .

At Carnegie Mellon, we value the whole package when extending offers of employment. Beyond credentials, we evaluate the role and responsibilities, your valuable work experience, and the knowledge gained through education and training. We appreciate your unique skills and the perspective you bring. Your journey with us is about more than just a job; it’s about finding the perfect fit for your professional growth and personal aspirations.

Are you interested in an exciting opportunity with an exceptional organization?! Apply today!

Location

Arlington, VA, Pittsburgh, PA

Job Function

Software/Applications Development/Engineering

Position Type

Staff – Regular

Full Time/Part time

Full time

Pay Basis

Salary

More Information:

  • Please visit “Why Carnegie Mellon (http://www.cmu.edu/jobs/why-cmu/index.html) ” to learn more about becoming part of an institution inspiring innovations that change the world.

  • Click here (https://www.cmu.edu/jobs/benefits-at-a-glance/) to view a listing of employee benefits

  • Carnegie Mellon University is an Equal Opportunity Employer/Disability/Veteran .

  • Statement of Assurance (https://www.cmu.edu/policies/administrative-and-governance/statement-of-assurance.html)

Interested in a career with Carnegie Mellon University but not finding anything that currently aligns with your interests, background, or experience? Learn how to sign up for Job Alerts (https://www.cmu.edu/jobs/external-applicants.html#job-alerts) through your candidate profile.

If your heart is in your work, come work with us. Carnegie Mellon University isn’t just one of the world’s most renowned educational institutions – it’s also a hotspot for some of the most talented doers, dreamers, and difference-makers on the planet. When you join our staff, you’ll become an important part of our mission to create a healthier, safer, and more just life for all. No matter what your role or location, you’ll connect and collaborate with dedicated, passionate colleagues – and you’ll have the satisfaction of delivering work that truly matters.

We cultivate a vibrant, welcoming environment where everyone is valued and encouraged to contribute and achieve. In addition to competitive benefits and a robust support network, you’ll have access to many tools and resources to sharpen your abilities and professional skills, as well as opportunities to engage and share perspectives with a dynamic and inspiring community of uniquely talented staff, faculty, students, and alumni.

The future is awaiting your expertise and intellect. Come join the architects of what’s next. Apply now.

Learn more about Student Employment (https://www.cmu.edu/sfs/student-employment/index.html) .

Please see Faculty Careers. (https://www.cmu.edu/faculty-office/faculty-recruitment/faculty-careers.html)

For technical assistance, email HR Services (hr-help@andrew.cmu.edu) or call 412-268-4600.

If you are an individual with a disability and you require assistance with the job application process, please email Equal Opportunity Services (employeeaccess@andrew.cmu.edu) or call 412-268-3930.

Prospective Employee Disclosures (https://www.cmu.edu/jobs/disclosures/index.html)


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