1

Staff Machine Learning Engineer Jobs in Pennsylvania

* Staff Applied Machine Learning Engineer * Remote (must be based in USA) * Work Authorization: ship or required due to government contract requirements * $230-280,000 base + Equity + Benefits About ...

As a Machine Learning Engineer in the Machine Intelligence Neural Design (MIND) team, you'll have the opportunity to be part of a leading ML innovation organization that develops a wide range of ...

New

As a Machine Learning Engineer in the Machine Intelligence Neural Design (MIND) team, you'll have the opportunity to be part of a leading ML innovation organization that develops a wide range of ...

As a Machine Learning Engineer in the Machine Intelligence Neural Design (MIND) team, you'll have the opportunity to be part of a leading ML innovation organization that develops a wide range of ...

Senior Machine Learning Engineer

Malvern, PA ยท On-site

$120K - $158K/yr

We are assisting our client in hiring for a Senior Machine Learning Engineer. Our client is an established SaaS company serving banks, credit unions, and fintechs. Their cloud-based platform helps ...

Senior Machine Learning Engineer

Malvern, PA ยท On-site

$102K - $140K/yr

Design, build, and maintain end-to-end machine learning pipelines from research through production deployment. * Engineer scalable training, inference, and retraining workflows using AWS SageMaker.

next page

Showing results 1-20

Staff Machine Learning Engineer information

See Pennsylvania salary details

$23.1K

$99.6K

$193K

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

As of Aug 14, 2026, the average yearly pay for staff machine learning engineer in Pennsylvania is $99,568.00, according to ZipRecruiter salary data. Most workers in this role earn between $69,200.00 and $125,300.00 per year, depending on experience, location, and employer.

What are the typical collaboration and leadership responsibilities for a staff machine learning engineer?

As a Staff Machine Learning Engineer, you often serve as a technical leader, partnering with cross-functional teams including data scientists, product managers, and software engineers to develop and deploy machine learning solutions. You will mentor junior engineers, conduct code reviews, and help establish best practices for model development and deployment. In addition to hands-on technical work, you may be responsible for evaluating new tools, contributing to the broader ML strategy, and facilitating knowledge sharing sessions. This collaborative and leadership-focused approach helps ensure consistency, quality, and innovation across machine learning projects.

What are the key skills and qualifications needed to thrive in the staff machine learning engineer position, and why are they important?

To thrive as a Staff Machine Learning Engineer, you need deep expertise in machine learning algorithms, software engineering, data analysis, and typically a strong academic background in computer science or related fields. Experience with Python, TensorFlow, PyTorch, cloud platforms, and a track record of delivering production-level ML systems are crucial, as are advanced degrees or relevant certifications. Strong leadership, communication, and mentoring skills help you effectively guide teams and collaborate across departments. These competencies are essential for designing robust ML solutions, leading technical initiatives, and ensuring successful project delivery in complex organizational environments.

What is a staff machine learning engineer?

A Staff Machine Learning Engineer is a senior-level technical role responsible for designing, deploying, and optimizing machine learning models at scale. They provide technical leadership, mentor other engineers, and drive best practices in ML system architecture. This role often involves collaborating with cross-functional teams, improving model performance, and ensuring the reliability of machine learning solutions in production. Staff ML Engineers typically have deep expertise in algorithms, data infrastructure, and engineering processes. Their work focuses on solving complex problems and influencing the broader ML strategy within an organization.

What job categories do people searching Staff Machine Learning Engineer jobs in Pennsylvania look for?

The top searched job categories for Staff Machine Learning Engineer jobs in Pennsylvania are:

Infographic showing various Staff Machine Learning Engineer job openings in Pennsylvania as of August 2026, with employment types broken down into 2% As Needed, 72% Full Time, 21% Part Time, 1% Temporary, 3% Contract, and 1% Nights. Highlights an 96% Physical, 2% Hybrid, and 2% Remote job distribution, with an average salary of $99,568 per year, or $47.9 per hour.

Staff Machine Learning Engineer

LHi Group Ltd

Calumet, PA โ€ข On-site

$280K/yr

Other

Posted 8 days ago


Job description

  • Staff Applied Machine Learning Engineer
  • Remote (must be based in USA)
  • Work Authorization: ship or required due to government contract requirements
  • $230-280,000 base + Equity + Benefits

About the Opportunity
Our client is a rapidly growing, venture-backed AI company building secure, enterprise-grade AI solutions for highly regulated industries. Their platform helps organizations unlock the value of complex data by embedding AI into mission-critical workflows, improving decision-making, operational efficiency, and knowledge discovery.
As the company continues to scale, they are investing heavily in next-generation AI capabilities, including search, knowledge exploration, semantic reasoning, and agentic AI. This is an opportunity to join a high-caliber engineering team tackling technically challenging problems at production scale while helping shape the future direction of the platform.
The Role
As a Staff Applied Machine Learning Engineer, you will design, build, and deploy advanced machine learning solutions that power intelligent search, knowledge exploration, and AI-driven workflows.
You'll work closely with product, platform, and engineering teams to develop production-grade ML systems, combining strong software engineering fundamentals with expertise in modern AI techniques. This is a highly technical individual contributor role with significant ownership and influence over architectural decisions.
Responsibilities
  • Lead the design, development, and deployment of machine learning models for large-scale production systems.
  • Design and build intelligent search and knowledge exploration capabilities using modern ML techniques.
  • Develop systems involving knowledge graphs, semantic representations, and advanced entity understanding.
  • Collaborate with engineering and product teams to deliver end-to-end machine learning solutions.
  • Evaluate model performance, runtime efficiency, and scalability in production environments.
  • Communicate technical decisions, trade-offs, and recommendations to both technical and non-technical stakeholders.
  • Build high-quality enterprise software while maintaining a fast pace of delivery.
  • Take ownership of projects from design through implementation, deployment, and ongoing support.
  • Troubleshoot and support distributed production systems.
  • Stay current with advances in AI and machine learning and apply emerging techniques where appropriate.

Required Qualifications
  • ship or required.
  • Bachelor's or Master's degree in Computer Science, Machine Learning, NLP, or a related field. A PhD is strongly preferred.
  • 10+ years of experience building and deploying production machine learning systems.
  • Strong background in Natural Language Processing (NLP), information retrieval, or semantic search.
  • Experience designing and supporting knowledge graph or semantic representation systems.
  • Proven experience building and deploying Agentic AI systems, including orchestration, tool use, reasoning workflows, and context management.
  • Strong software engineering skills with experience building scalable distributed systems.
  • Experience working with production ML systems throughout their lifecycle.
  • Excellent communication and cross-functional collaboration skills.
  • Experience leveraging modern AI tools to improve engineering productivity.
  • Demonstrated curiosity, adaptability, and a continuous learning mindset.

Preferred Qualifications
  • PhD in Computer Science, Machine Learning, Artificial Intelligence, NLP, or a related discipline.
  • Experience working in startup or high-growth environments, particularly building 0?1 products.
  • Familiarity with Kubernetes and cloud-native infrastructure.
  • Experience integrating machine learning models into large-scale enterprise platforms.

Why Join?
  • Join a fast-growing, well-funded AI company solving complex real-world problems.
  • Work on cutting-edge technologies including Agentic AI, NLP, search, knowledge graphs, and semantic reasoning.
  • Collaborate with an experienced engineering team that values technical excellence, ownership, and innovation.
  • Competitive compensation and meaningful pre-IPO equity.
  • Fully remote position within the United States.