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Machine Learning Engineer Jobs in Pittsburgh, PA

Skild AI

Machine Learning Engineer

Pittsburgh, PA

$100K - $300K/yr

Machine Learning Engineer San Mateo, Pittsburgh Company Overview At Skild AI, we are building the world's first general purpose robotic intelligence that is robust and adapts to unseen scenarios ...

Motional

Staff Machine Learning Engineer

Pittsburgh, PA · On-site +1

As a Staff Machine Learning Engineer, you will serve as a technical leader defining the roadmap and architecture for the machine learning systems that power our data discovery and model improvement ...

Motional

Staff Machine Learning Engineer

Pittsburgh, PA · On-site +1

As a Staff Machine Learning Engineer, you will serve as a technical leader defining the roadmap and architecture for the machine learning systems that power our data discovery and model improvement ...

Motional

Staff Machine Learning Engineer

Pittsburgh, PA · On-site

As a Staff Machine Learning Engineer, you will serve as a technical leader defining the roadmap and architecture for the machine learning systems that power our data discovery and model improvement ...

Cmu

Machine Learning Engineer - Autonomy Lab

Pittsburgh, PA · On-site

$99K - $131K/yr

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 ...

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

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 9, 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.
More about Machine Learning Engineer jobs
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 job categories do people searching Machine Learning Engineer jobs in Pittsburgh, PA look for? The top searched job categories for Machine Learning Engineer jobs in Pittsburgh, PA 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:
Machine Learning Engineer jobs near you
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

Skild AI

Pittsburgh, PA

$100K - $300K/yr

Other

Posted 3 days ago

Job description

Machine Learning Engineer

San Mateo, Pittsburgh

Company Overview

At Skild AI, we are building the world's first general purpose robotic intelligence that is robust and adapts to unseen scenarios without failing. We believe massive scale through data-driven machine learning is the key to unlocking these capabilities for the widespread deployment of robots within society. Our team consists of individuals with varying levels of experience and backgrounds, from new graduates to domain experts. Relevant industry experience is important, but ultimately less so than your demonstrated abilities and attitude. We are looking for passionate individuals who are eager to explore uncharted waters and contribute to our innovative projects.

Position Overview

We are looking for a Machine Learning Engineer to be responsible for designing and implementing cutting-edge reinforcement learning algorithms, conducting experiments, and optimizing these models to perform efficiently in real-world robotic environments. This will require close collaboration with our robotics, research, and engineering team. Your work will directly impact the development of intelligent, adaptable robots capable of learning and performing complex tasks autonomously.

Responsibilities
  • Develop and implement state-of-the-art reinforcement learning algorithms for robotic applications.
  • Design and conduct experiments to train RL models and conduct real-world tests.
  • Collaborate closely with researchers to explore novel methods of scaling up reinforcement learning model training.
  • Communicate effectively with inference, application, and deployment engineers to integrate RL models into robotic systems and iterate on methods to enable robust deployment.
  • Analyze and interpret experimental results, iterating on model design to achieve desired performance.
  • Stay up-to-date with the latest research and advancements in reinforcement learning.
Preferred Qualifications
  • BS, MS or higher degree in Computer Science, Robotics, Engineering or a related field, or equivalent practical experience.
  • Proficiency in Python, C++, or similar and at least one deep learning library such as PyTorch, TensorFlow, JAX, etc.
  • Deep understanding and practical experience with various reinforcement learning algorithms and techniques (model-free, model-based, multi-task, hierarchical, multi-agent, etc.).
  • Strong background in algorithms, data structures, and software engineering principles.
  • Experience with physics simulation engines and tools for training RL.
  • Deep understanding of state-of-the-art machine learning techniques and models.
  • Extensive industry experience with reinforcement learning and robotic systems.

Base Salary Range

$100,000 - $300,000 USD

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