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Machine Learning Engineer Opt Jobs in Pittsburgh, PA

... 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 ...

Machine Learning Tutor

Pittsburgh, PA ยท 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 ...

Showing results 41-60

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 Aug 14, 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 is a machine learning engineer?

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.

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 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 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:

Director of Machine Learning

Gather AI

Pittsburgh, PA โ€ข 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:
โ€ข Define and own the ML strategy and technical roadmap for Gather AI, aligned with product and business objectives
โ€ข Lead and grow the Machine Learning and FPT teams, establishing a culture of rigor, experimentation, and production-quality delivery
โ€ข Drive improvements to core computer vision models (object detection, segmentation, OCR) used across our drone and MHE Vision products
โ€ข Build out MLOps infrastructure โ€” model training pipelines, deployment, monitoring, and CI/CD for ML workloads
โ€ข Collaborate with the Director of Cloud Engineering and Director of Autonomy to ensure ML systems integrate seamlessly into the broader platform
โ€ข Partner with Product and Operations to translate customer needs into ML-driven product capabilities
Qualifications:
Required:
โ€ข 10+ years building and scaling production ML or computer vision systems
โ€ข 5+ years managing and growing ML engineering teams
โ€ข Deep expertise in computer vision: object detection, image segmentation, OCR, and CNN architectures
โ€ข Strong Python and PyTorch (or TensorFlow) proficiency, plus a track record of shipping ML models to production at scale
โ€ข MS or PhD in Computer Science, Machine Learning, or a related field (strong industry track record considered in lieu of advanced degree)
Preferred:
โ€ข Experience with drone, robotics, or autonomous systems perception
โ€ข Edge ML deployment experience (ONNX, TensorRT, mobile/embedded inference)
โ€ข Familiarity with warehouse, logistics, or supply chain domain
โ€ข 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.