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Machine Learning Engineer Opt Jobs in Pittsburgh, PA

As a machine learning engineer in the AI for Autonomy Lab, you willidentify, shape, apply, conduct, and lead engineering research that matches critical U.S. government needs. The AI for Autonomy Lab ...

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Engineer Pittsburgh, Pennsylvania, United States Company Description Govini transforms Defense Acquisition from an outdated manual process to a software-driven strategic ...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

... 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 Opt information

See Pittsburgh, PA salary details

$30.6K

$125K

$187.9K

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

As of Jun 12, 2026, the average yearly pay for machine learning engineer opt in Pittsburgh, PA is $125,011.00, 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 into production environments. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, reliable systems that organizations can use to make predictions or automate tasks. Their responsibilities include data preprocessing, choosing appropriate algorithms, model training, and ensuring the model's performance in real-world applications. Machine Learning Engineers often collaborate with data scientists, data engineers, and product teams to deliver intelligent solutions.

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

AspectMachine Learning Engineer OptData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; certifications in ML toolsBachelor's or Master's in CS, Statistics, or related fields; data analysis certifications
Work EnvironmentDevelops, tests, and deploys ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, AI startups, e-commerce, financeResearch institutions, tech firms, consulting, finance
Common Search & ComparisonOften compared for technical skills and deployment focusCompared for data analysis and business insights

Machine Learning Engineers Opt focus on deploying scalable ML models in production environments, while Data Scientists primarily analyze data and develop models for insights. Both roles require strong technical skills, but their core responsibilities differ in application and deployment.

Is a machine learning engineer still in demand?

Yes, machine learning engineers are in high demand due to the growing adoption of AI and data-driven solutions across industries. They are sought after for their skills in programming, data analysis, and familiarity with tools like Python, TensorFlow, and cloud platforms, making this a strong career choice for those with relevant expertise.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as AI advances because they develop and refine AI models, requiring specialized skills in programming, data analysis, and domain knowledge. Jobs that involve complex problem-solving, creativity, and emotional intelligence, such as healthcare professionals, educators, and skilled tradespeople, are also expected to persist despite AI automation. Continuous learning and adapting to new tools and technologies will be essential for job security across many fields.

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 a solid background in mathematics, statistics, and programming (especially Python), typically supported by a degree in computer science, engineering, or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch), data processing tools, and cloud platforms, along with relevant certifications, is highly valuable. Strong problem-solving ability, collaboration, and effective communication are standout soft skills in this role. These skills and qualities ensure the successful development, deployment, and integration of machine learning solutions that drive business value.

What is a $900,000 AI job?

A $900,000 AI-related job typically refers to high-level roles such as senior machine learning engineers, AI research directors, or chief AI officers, often in large tech companies or specialized firms. These positions usually require advanced skills in machine learning, deep learning, and data science, along with extensive experience and leadership responsibilities.

What are some common challenges Machine Learning Engineers face when deploying models to production environments?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, handling data drift, and integrating models seamlessly with existing systems when deploying to production. Monitoring model performance in real time and retraining models as new data becomes available are also critical tasks. Collaboration with data engineers and DevOps teams is essential to address infrastructure and deployment hurdles while maintaining model accuracy and reliability.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-paying industries such as finance or tech, can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially at large tech companies or startups with significant funding.
What are popular job titles related to Machine Learning Engineer Opt jobs in Pittsburgh, PA? For Machine Learning Engineer Opt jobs in Pittsburgh, PA, the most frequently searched job titles are:
What cities near Pittsburgh, PA are hiring for Machine Learning Engineer Opt jobs? Cities near Pittsburgh, PA with the most Machine Learning Engineer Opt job openings:

Machine Learning Engineer - Autonomy Lab

Cmu

Pittsburgh, PA

$99K - $131K/yr

Full-time

Posted 22 days ago


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) toprovideleap-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 willidentify, shape, apply, conduct, and lead engineering research that matches critical U.S. government needs. The AI for Autonomy Lab researches anddemonstratesthe 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 whilemulti-tasking-sometimesunder 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.

Location

Arlington, VA, Pittsburgh, PA

Job Function

Software/Applications Development/Engineering

Position Type

Staff - Regular

Full time/Part time

Full time

Pay Basis

SalaryMore Information:
  • Please visit "Why Carnegie Mellon" to learn more about becoming part of an institution inspiring innovations that change the world.

  • Click here to view a listing of employee benefits

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

  • Statement of Assurance


About CMU

Sourced by ZipRecruiter

Industry

Offices of mental health practitioners

Company size

201 - 500 Employees

Headquarters location

Harrisburg, PA, US