ML Software Engineer Jobs in Pittsburgh, PA
ML Software Engineer jobs in Pittsburgh are concentrated in Oakland, Shadyside, and the Strip District, driven by demand across healthcare AI, robotics, and autonomous systems. Carnegie Mellon University, Stack AV, and Aurora are among those actively hiring right now. See the openings below and apply to the ones that match your experience.
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At the SEI AI Division, we conduct research in applied artificial intelligence and the engineering questions related to the practical design and implementation of 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 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, and maintaining AI capabilities
identify and investigate emerging AI and AI-adjacent technologies that are rapidly transforming the technology landscape
Are you creative, curious, energetic, collaborative, technology-focused, and hard-working? Are you interested in making a difference by bringing innovation to government organizations and beyond? Apply to join our team.
Overview : As a Senior Machine Learning Engineer, you will specialize in engineering solutions that support research into the vulnerabilities of AI and ML algorithms and securing against those vulnerabilities.
The Secure AI Lab within the SEI’s AI Division focuses on improving the security and robustness of AI systems. As part of the world-class research community at Carnegie Mellon University, the Secure AI Lab conducts and applies cutting-edge research to protect AI systems from adversaries who aim to manipulate the system to learn, do, or reveal something it isn’t supposed to.
The Secure AI Lab consists of machine learning research scientists, machine learning engineers, and software developers who work together to solve problems in the following areas:
Counter AI Research : Study threat models targeting AI and ML algorithms , understand the behaviors of AI algorithms, identify weak points, and design novel ways to subvert AI and ML systems .
AI and ML Algorithm Defense Research: Creat e practical mitigations and defenses for observed attacks affecting AI and ML algorithms and evaluate the effectiveness of defensive techniques .
Applied Adversarial Machine Learning: Advance the state of the art in adversarial machine learning by developing and transitioning capabilities to government sponsors.
As an engineer, you will solve problems for government sponsors by analyzing, designing, and building responsible AI systems.
Your day-to-day engineering tasks will include:
Identifying and i nvestigating emerging AI and AI-adjacent technologies.
Defining and r efining processes, practices, and tools for working with AI.
Designing and b uilding well-engineered prototypes of AI systems.
Transitioning and p roviding guidance on AI capabilities to government sponsors.
Duties
Building Machine Learning Models and Systems: You will work with machine learning frameworks such as TensorFlow, PyTorch , Torch, and Caffe and modern programming languages including Python, C/C++, and Java. You will build and work with dat a pipelines, ETL processes, and backend systems. You will work with, extend, and implement state-of-the-art machine learning methods.
Technical Experimentation: You will experiment with modern and emerging machine learning frameworks, methods, and algorithms in application domains that include computer vision, natural language processing, planning and scheduling, robot control, and engineering safe, trusted, and reliable machine learning systems.
Test ing and evaluat ion . You'll conduct rapid prototyping to demonstrate and evaluate technologies in relevant environments. You'll evaluate systems for performance and security. You'll test capabilities using novel testing and analysis techniques.
Collaborat ion . You'll actively participate on teams of developers, researchers, designers, and technical leads. You'll collaborate with researchers and our government customers to understand challenges, needs, and possible solutions .
Mentoring. You'll contribute to improving the overall technical capabilities of the Division by mentoring and teaching others, participating in design (software and otherwise) sessions, and sharing insights and wisdom across the SEI.
Knowledge and Experience
Comprehensive knowledge of machine learning ; previous experience in adversarial machine learning desirable but not required
A track record of using well-established engineering practices to solve difficult problems
An understanding of how to convert research results in to functioning prototypes or capabilities
Experience l ead ing technical projects in novel areas with limited previous work to build upon
Strong written and verbal communication skills ; able to convey complex technical ideas in a layperson’s terms
Ample experience with publishing written or technical artifacts showcasing your work
Strong collaboration skills for working with colleagues and sponsors
Willing ness to guide and mentor junior team members
Requirements
A bachelor’s degree in computer science, statistics, machine learning, electrical engineering, or related discipline with ten (10) years of experience; OR MS in the same fields with eight (8) years of experience; OR PhD with five (5) years of experience.
Willingness to work onsite 5 days per week at SEI offices in Pittsburgh, PA or Arlington, VA.
Be able to obtain and maintain an active Department of War security clearance.
Willing to travel up to 25% of the time to locations outside of your home location. Travel sites include SEI offices in Pittsburgh and Washington, D.C., sponsor sites, and conferences.
Joining the CMU team opens the door to an array of exceptional benefits.
Benefits eligible employees enjoy a wide array of benefits including comprehensive medical, prescription, dental, and vision insurance as well as a generous retirement savings program with employer contributions. Unlock your potential with tuition benefits , take well-deserved breaks with ample paid time off and observed holidays , 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 to help navigate childcare needs, fitness center access , and much more!
For a comprehensive overview of the benefits available, explore our Benefits page .
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, PAJob Function
Software/Applications Development/EngineeringPosition Type
Staff – RegularFull Time/Part time
Full timePay Basis
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Who's Hiring



Top Industries Hiring
- Technology & Software
- Automotive
- Manufacturing
- Artificial Intelligence
ML Software Engineer Jobs in Pittsburgh: Frequently Asked Questions
How do I get a ml software engineer job in Pittsburgh?
Focus your search on Pittsburgh's core ML hubs: Oakland's university-adjacent research corridor, the Strip District's tech startup cluster, and healthcare systems in Shadyside and Squirrel Hill. Employers here prioritize experience with large-scale model training, PyTorch or TensorFlow, and applied research backgrounds. Candidates who have worked on robotics, medical imaging, or autonomous systems have a real edge in this market, given Pittsburgh's concentration in those domains.
Which companies hire ml software engineers in Pittsburgh?
Pittsburgh ml software engineer roles are posted by Carnegie Mellon University, Stack AV, and Aurora and others right now, based on current listings on Migrate Mate as of July 2026. Pittsburgh's employer mix leans heavily toward research-driven tech companies, university spinouts, large healthcare networks, and defense and robotics contractors.
Are there remote ml software engineer jobs in Pittsburgh?
Yes, ml software engineering is well-suited to remote and hybrid arrangements since the core work involves coding, model development, and data pipelines rather than on-site equipment. About 38% of ml software engineer openings tied to Pittsburgh are remote or hybrid as of July 2026, with the remainder typically requiring on-site collaboration for research teams or lab-integrated roles. Research-oriented positions at Pittsburgh's tech and healthcare employers are most likely to offer flexibility.
How can I get a ml software engineer job in Pittsburgh with little or no experience?
The most realistic entry path in Pittsburgh is through research assistant or junior ML engineer roles at Carnegie Mellon University-affiliated labs or university hospital AI teams, where applied project experience substitutes for industry tenure. Pittsburgh's robotics and autonomous vehicle companies also hire ML associates and data science interns who transition into engineering roles. Building a portfolio around computer vision, NLP, or reinforcement learning, areas central to Pittsburgh's dominant industries, sharpens your candidacy significantly.
Which industries hire the most ml software engineers in Pittsburgh?
The sectors hiring the most ml software engineers in Pittsburgh are Technology & Software, Automotive, and Manufacturing, based on current listings on Migrate Mate as of July 2026. Pittsburgh's deep roots in robotics research, its large academic medical centers, and its growing autonomous systems ecosystem make these sectors the consistent drivers of local ML engineering demand.
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