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Machine Learning Engineer Jobs in Pittsburgh, PA

Gather AI

Director of Machine Learning

Pittsburgh, PA · On-site

... 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 ...

Varsity Tutors

Machine Learning Tutor

Pittsburgh, PA · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

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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 Aug 15, 2026, the average yearly pay for machine learning engineer 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 is a machine learning engineer?

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.

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 August 2026, with employment types broken down into 79% Full Time, and 21% Contract. Highlights an 100% In-person job distribution, with an average salary of $125,011 per year, or $60.1 per hour.

Director of Machine Learning

Gather AI

Pittsburgh, PA • On-site

Full-time

Re-posted 14 days ago

Job description

Job Summary:
Gather AI is pioneering a new era of warehouse intelligence with innovative software that utilizes autonomous drones for real-time data capture. They are seeking a Director of Machine Learning to define the ML strategy, lead the computer vision organization, and enhance the company's ML capabilities to support their vision-powered platform.
Responsibilities:
• Define and own the ML strategy and technical roadmap for Gather AI, aligned with product and business objectives
• Lead and grow the Machine Learning and FPT teams, establishing a culture of rigor, experimentation, and production-quality delivery
• Drive improvements to core computer vision models (object detection, segmentation, OCR) used across our drone and MHE Vision products
• Build out MLOps infrastructure — model training pipelines, deployment, monitoring, and CI/CD for ML workloads
• Collaborate with the Director of Cloud Engineering and Director of Autonomy to ensure ML systems integrate seamlessly into the broader platform
• Partner with Product and Operations to translate customer needs into ML-driven product capabilities
Qualifications:
Required:
• 10+ years building and scaling production ML or computer vision systems
• 5+ years managing and growing ML engineering teams
• Deep expertise in computer vision: object detection, image segmentation, OCR, and CNN architectures
• Strong Python and PyTorch (or TensorFlow) proficiency, plus a track record of shipping ML models to production at scale
• MS or PhD in Computer Science, Machine Learning, or a related field (strong industry track record considered in lieu of advanced degree)
Preferred:
• Experience with drone, robotics, or autonomous systems perception
• Edge ML deployment experience (ONNX, TensorRT, mobile/embedded inference)
• Familiarity with warehouse, logistics, or supply chain domain
• Experience with AWS or GCP ML services (SageMaker, Vertex AI)
Company:
We deliver the foundational intelligence layer for the intralogistics industry. Founded in 2017, the company is headquartered in Pittsburgh, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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