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Freelance Machine Learning Engineer Jobs in Pittsburgh, PA

We are looking for a Machine Learning Systems Engineer to join our ML Acceleration team. In this role, you will be responsible for the core systems that enable our researchers to train frontier ...

About the Team You'll lead the Machine Learning and FPT teams, working closely with the Director of Cloud Engineering and Director of Autonomy. Cross-departmentally, you'll collaborate with Product ...

About the Team You'll lead the Machine Learning and FPT teams, working closely with the Director of Cloud Engineering and Director of Autonomy. Cross-departmentally, you'll collaborate with Product ...

... Cloud Engineering and Director of Autonomy to ensure ML systems integrate seamlessly into the ... Machine Learning, or a related field (strong industry track record considered in lieu of advanced ...

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Freelance Machine Learning Engineer information

See Pittsburgh, PA salary details

$14

$46

$128

How much do freelance machine learning engineer jobs pay per hour?

As of Aug 23, 2026, the average hourly pay for freelance machine learning engineer in Pittsburgh, PA is $46.31, according to ZipRecruiter salary data. Most workers in this role earn between $23.56 and $59.95 per hour, depending on experience, location, and employer.

What does a freelance machine learning engineer do?

A Freelance Machine Learning Engineer designs, develops, and implements machine learning models and algorithms for clients on a project basis. They work independently to analyze data, build predictive models, and help businesses solve complex problems using AI and machine learning techniques. Their responsibilities may also include data preprocessing, model evaluation, and deploying solutions into production environments. Freelance Machine Learning Engineers often collaborate remotely with teams and must manage their own schedules and client relationships.

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

To thrive as a Freelance Machine Learning Engineer, you need expertise in programming (especially Python), a solid grasp of machine learning algorithms, and a relevant academic background such as a degree in computer science, mathematics, or engineering. Familiarity with frameworks like TensorFlow or PyTorch, cloud platforms (AWS, GCP, Azure), and experience with version control systems are typically required. Strong problem-solving, self-management, and client communication skills help set successful freelancers apart. These competencies are crucial for delivering effective solutions, managing projects independently, and building client trust in a competitive market.

How do freelance machine learning engineers typically manage client expectations and project scopes?

Freelance machine learning engineers often work with clients who may not have a deep technical understanding of AI or data science. A common challenge is clearly defining the project scope and deliverables at the outset, ensuring both parties understand what is feasible given the data, time, and budget constraints. Successful freelancers use regular progress updates, milestone-based deliverables, and transparent communication to manage expectations and avoid scope creep. Building trust through clear documentation and setting realistic timelines also helps foster long-term client relationships.

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

AspectFreelance Machine Learning EngineerData Scientist
CredentialsTypically requires a degree in computer science, data science, or related fields; certifications in machine learning or AI are a plusUsually holds a degree in statistics, data science, or related areas; certifications in data analysis or visualization are common
Work EnvironmentIndependent, project-based work often remotely for various clientsOften employed full-time in organizations or consulting roles, sometimes freelance
Industry UsageUsed across tech, finance, healthcare, and startups for deploying ML modelsApplied in research, analytics, and strategic decision-making across industries

Freelance Machine Learning Engineers focus on developing and deploying ML models independently for diverse clients, while Data Scientists analyze data to extract insights, often working within organizations. Both roles require strong technical skills, but their work scope and environment differ significantly.

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 Freelance Machine Learning Engineer jobs in Pittsburgh, PA?

For Freelance Machine Learning Engineer jobs in Pittsburgh, PA, the most frequently searched job titles are:

What job categories do people searching Freelance Machine Learning Engineer jobs in Pittsburgh, PA look for?

The top searched job categories for Freelance Machine Learning Engineer jobs in Pittsburgh, PA are:

What cities near Pittsburgh, PA are hiring for Freelance Machine Learning Engineer jobs?

Cities near Pittsburgh, PA with the most Freelance Machine Learning Engineer job openings:

Infographic showing various Freelance Machine Learning Engineer job openings in Pittsburgh, PA as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $96,334 per year, or $46.3 per hour.

Senior Machine Learning Engineer - Mission Innovation Lab

Carnegie Mellon University

Pittsburgh, PA • On-site

$101K - $139K/yr

Full-time

Re-posted 3 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

70th of 622 rated colleges and universities


Job description

Job Summary:
Carnegie Mellon University is a leading institution in artificial intelligence research, and they are seeking a Senior Machine Learning Engineer for their Mission Innovation Lab. In this role, you will lead independent applied-research projects, focusing on developing and implementing state-of-the-art machine learning models to support defense and national security missions.
Responsibilities:
• Design, implement, and evaluate state‑of‑the‑art ML models (computer‑vision, NLP, planning, etc.) using frameworks such as TensorFlow, PyTorch, Torch, or Caffe.
• Build and maintain robust data pipelines, ETL processes, and backend services in Python, C/C++, and Java.
• Lead rapid‑prototyping efforts, translate research results into operational prototypes, and test for performance, robustness, and security.
• Define and refine DevSecOps practices for ML (model registries, containerized deployment, continuous integration/continuous delivery, security scanning).
• Mentor junior team members, collaborate with researchers, government customers, and other engineers, and contribute to technical strategy for the lab.
Qualifications:
Required:
• B.S. in Computer Science, Electrical Engineering, Statistics, or related field with ≥10 years of experience; OR M.S. with ≥8 years; OR Ph.D. with ≥5 years of relevant experience.
• Ability to obtain and maintain an active Department of War security clearance.
• You must be able and willing to work onsite 5 days per week at an SEI office in either Pittsburgh, PA or Arlington, VA.
• Strong experience in one or more programming language such as Python, C/C++, and Java; comfortable developing production-grade code and APIs.
• Solid understanding of ML theory, statistical learning, and common algorithms.
• Hands-on experience with TensorFlow, PyTorch, Torch, Caffe, or similar deep-learning libraries.
• Familiarity with CI/CD pipelines, container orchestration (Docker/Kubernetes), model versioning, and security-focused tooling.
Preferred:
• Proven track record of independent applied-research projects that resulted in demonstrable prototypes or operational capabilities.
• Publications or open-source contributions in AI and ML, especially in adversarial or robust ML.
• Experience working on defense or other high-impact government programs.
• Ability to quickly learn emerging AI and ML technologies and translate them into mission-relevant solutions.
• Deep technical knowledge of modern ML methods and ability to extend them to novel domains.
• Excellent written and verbal communication skills; capable of presenting complex ideas to technical and non-technical audiences.
• Strong collaborative mindset; experience working in interdisciplinary teams and mentoring peers.
• High degree of scientific curiosity and a proactive, self-directed work style.
Company:
Carnegie Mellon University is a research university offering programs and research across engineering, science, arts, and business. Founded in 1900, the company is headquartered in Pittsburgh, USA, with a team of 5001-10000 employees. The company is currently Late Stage.

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