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Machine Learning Engineer Jobs in California, PA

Synopsys Inc

Agentic AI Engineer

Canonsburg, PA · On-site

... and Machine Learning with 2+ years of hands-on experience is a plus • Demonstrable experience ... Company : Synopsys is the leader in engineering solutions from silicon to systems, enabling ...

Alstom

AI & Test Automation Lead

Pittsburgh, PA

$44 - $60/hr

Degree in Engineering, Computer Engineering, Computer Science, or similar field. , * Experience or understanding of applying AI/ML for test automation, such as using machine learning or natural ...

Kurt J Lesker Company

Machine Apprentice

Clairton, PA · On-site

$16 - $20.50/hr

Are you passionate about machining , innovation , and continuous learning ? Join our state ... Work with Machinists, Project Managers and Engineers to solve problems and improve processes

Apply Early

Kurt J Lesker

Machine Apprentice

Jefferson Hills, PA · On-site

$16 - $20.50/hr

Are you passionate about machining , innovation , and continuous learning ? Join our state ... Work with Machinists, Project Managers and Engineers to solve problems and improve processes

SMC Region USC

Regulatory Engineer

Brier Hill, PA

We offer competitive wages and benefits , strong support for learning and professional development ... Reviews spare parts recommendations and develop accuracy of Machine Life Operating Costs (MLOC ...

Alstom

Methods Engineer

West Mifflin, PA · On-site

Could you be the full-time onsite Methods Engineer in West Mifflin, PA (Pittsburgh area) we're ... Benefit from our investment in your development, through award-winning learning, * Benefit from a ...

Alstom

Methods Engineer

West Mifflin, PA · On-site

Could you be the full-time onsite Methods Engineer in West Mifflin, PA (Pittsburgh area) we're ... Benefit from our investment in your development, through award-winning learning, * Benefit from a ...

Alstom

Methods Engineer

West Mifflin, PA

Could you be the full-time onsite Methods Engineer in West Mifflin, PA (Pittsburgh area) we're ... Benefit from our investment in your development, through award-winning learning, * Benefit from a ...

Hitachi

Senior R&D Engineer

Mount Pleasant, PA · On-site

$101K - $139K/yr

Engineering & Science Job Schedule: Full time Remote: No The opportunity Join Hitachi Energy's High ... Grow through continuous learning, mentorship, and career development * Thrive in an inclusive ...

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Showing results 1-20

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

Machine Learning Engineer information

See California, PA salary details

$27.6K

$112.7K

$169.4K

How much do machine learning engineer jobs pay per year?

As of Jul 3, 2026, the average yearly pay for machine learning engineer in California, PA is $112,745.00, according to ZipRecruiter salary data. Most workers in this role earn between $88,900.00 and $135,700.00 per year, depending on experience, location, and employer.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-demand industries or companies can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially in tech giants or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

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.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as AI advances, as they develop and refine algorithms, models, and systems. Roles that require complex problem-solving, creativity, and domain expertise—such as healthcare professionals, data scientists, software developers, cybersecurity specialists, and AI ethics officers—are also expected to persist due to their reliance on human judgment and specialized knowledge. These jobs often involve skills that are difficult for AI to fully replicate or replace.

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 engineers make $300,000 a year?

Senior machine learning engineers and data scientists with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $300,000 or more annually, especially in high-cost-of-living areas or top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on business outcomes.

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 cities near California, PA are hiring for Machine Learning Engineer jobs? Cities near California, PA with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in California, PA as of June 2026, with employment types broken down into 1% As Needed, 87% Full Time, 10% Part Time, 1% Temporary, and 1% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $112,745 per year, or $54.2 per hour.
Applications Engineering, Staff Engineer - 16469

Applications Engineering, Staff Engineer - 16469

Synopsys

Canonsburg, PA • On-site, Remote

$112K/yr

Full-time

Posted 18 days ago

Job description

General Information
Job Title
Staff Engineer - AI/ML & Digital Twin
Job ID
16469
City
Canonsburg
State/Province
Pennsylvania
Date Posted
17-Mar-2026
Job Category
Engineering
Job Subcategory
Applications Engineering
Hire Type
Employee
Remote Eligible
Yes
Base Salary Range: $112000 - $168000
Descriptions & Requirements
Job Description and Requirements
We Are:
At Ansys, Part of Synopsys, we're the global leader in engineering simulation software, helping innovative companies solve complex design challenges. Our cutting-edge solutions power advancements across industries, from aerospace to consumer electronics. Join us and help shape the future of technology.
You Are:
You are a highly motivated engineer who thrives at the intersection of engineering simulation, data-driven methods, and AI/ML-enabled workflows. Your expertise allows you to operate confidently in customer-facing environments, translating complex, multidisciplinary challenges into scalable, practical solutions. You possess a strong foundation in simulation or engineering systems, hands-on experience with machine learning and automation, and the ability to engage as a trusted technical advisor.
You are energized by ambiguity, seeking out opportunities to enable new ways of working through automation, digital twins, and intelligent simulation workflows. You are passionate about democratizing simulation technology, making advanced capabilities accessible to a broader spectrum of users. Your approach is both strategic and hands-on, balancing high-level vision with detailed technical execution.
You excel in collaborative environments, working closely with cross-functional teams and customers to deliver impactful solutions. You advocate for innovation and continuous improvement, mentoring peers and championing best practices. Your communication skills enable you to distill complex concepts into actionable insights, fostering understanding across diverse audiences. Above all, you are driven by the desire to make a tangible impact in the world of engineering and technology.
What You'll Be Doing:
  • Lead and execute technical engagements across the customer lifecycle, including discovery, solution development, demonstrations, evaluations, and deployment.
  • Engage directly with customers to understand engineering workflows, data availability, and decision-making processes, translating them into AI-enabled simulation and digital engineering solutions.
  • Develop and implement differentiated solutions using technologies such as automation, reduced order modeling, optimization, simulation democratization, system-level modeling, and digital twins.
  • Integrate machine learning models within simulation and digital twin pipelines to improve prediction accuracy, reduce computational cost, and enable near real-time insights.
  • Define and deliver automated and scalable workflows that reduce reliance on expert-driven simulation and enable broader adoption across engineering teams.
  • Lead or contribute to first-of-a-kind or ambiguous use cases, including AI-assisted design exploration, surrogate modeling, and digital twin deployment.
  • Collaborate closely with product development teams to influence roadmap,validatenew capabilities, and improveusabilityof AI-enabled features.
  • Deliver professional services, training, and technical guidance to ensure successful adoption of advanced workflows.
  • Support pre-sales and technical marketing activities through demonstrations, evaluations, and industry engagement.

  • Mentor team members and contribute to the best internal practices around AI, automation, and simulation integration.

The Impact You Will Have:
  • Enable customers to transition from traditional simulation to AI-augmented and automated engineering workflows.
  • Reduce time-to-insight through surrogate modeling, optimization, and intelligent automation.
  • Expand access to simulation by supporting democratization across engineering and non-expert users.
  • Drive adoption of digital twin technologies for predictive and operational decision-making.
  • Influence product direction by connecting real-world use cases with next-generation AI-enabled capabilities.
  • Contribute to business growth through high-impact technical engagements and solution delivery.

What You'll Need:
  • MS (or PhD) in Engineering, Computer Science, Applied Mathematics, or relatedfield.
  • 5+ years of experience in engineering systems, simulation, or data-driven modeling.
  • Strong programming skills (Python preferred).
  • Experience working with modeling, simulation, optimization, or data-driven engineering workflows.
  • Strong analytical, problem-solving, and communication skills.
  • Ability tooperateeffectively in a customer-facing, consultative engineering role.
  • Proven experience in automation of engineering workflows or pipelines using tools such asoptiSLang,modeFrontier, HEEDS or equivalent.
  • Demonstratedexpertiseapplying machine learning techniques in engineering contexts, including surrogate modeling, regression methods, or neural networks (CNNs, RNNs, autoencoders).
  • Understanding ofprojection-based ROMs, dimensionality reduction, and feature engineering.
  • Knowledge of multi-fidelity system modeling using Twin Builder, Simulink,AMESimor equivalent.
  • Familiarity with deployment and operationalization of AI models, including integration into engineering workflows and use of frameworks such asPyTorch, TensorFlow, scikit-learn, Kubernetes, AWS/Azure equivalent.

  • Exposure tocloud or HPC-based environments for large-scale simulation or data processing.

Who You Are:
  • Customer-focused and able to build trusted relationships.
  • Comfortable working in ambiguous, fast-evolving technical environments.
  • A strong communicator who can translate complex concepts into actionable insights.
  • Self-driven, organized, and capable of managing multiple priorities.
  • A collaborative team player who contributes to a culture of learning and innovation.

The Team You'll Be A Part Of:
You will be part of a multidisciplinary engineering team focused on advancing industry adoption of simulation through AI, automation, digital twin, and MBSE technologies. The team collaborates closely with customers, product development, and go-to-market functions to deliver innovative, high-impact solutions.
Rewards and Benefits:
We offer a comprehensive range of health, wellness, and financial benefits to cater to your needs. Our total rewards include both monetary and non-monetary offerings. Your recruiter will provide more details about the salary range and benefits during the hiring process.
At Synopsys, we want talented people of every background to feel valued and supported to do their best work. Synopsys considers all applicants for employment without regard to race, color, religion, national origin, gender, sexual orientation, age, military veteran status, or disability.
In addition to the base salary, this role may be eligible for an annual bonus, equity, and other discretionary bonuses. Synopsys offers comprehensive health, wellness, and financial benefits as part of a competitive total rewards package. The actual compensation offered will be based on a number of job-related factors, including location, skills, experience, and education. Your recruiter can share more specific details on the total rewards package upon request. The base salary range for this role is across the U.S.
Synopsys logo

About Synopsys

Sourced by ZipRecruiter

Synopsys, Inc. (Nasdaq:SNPS) is the Silicon to Software partner for creative companies developing the electronic products and software applications we rely on every single day. As the world's 15th largest software company, Synopsys has a long history of being a global leader in electronic design automation (EDA) and semiconductor IP and is also growing its leadership in software quality and security solutions. Whether you're a system-on-chip (SoC) designer building advanced semiconductors, or a software developer writing applications that require the highest quality and security, Synopsys has the solutions needed to deliver exceptional, secure products for the era of connected everything. The company is headquartered in Mountain View, California, and has approximately 113 offices located throughout North America, South America, Europe, Japan, Asia and India. Since 1986, Synopsys has been at the heart of accelerating electronics innovation with engineers around the world having used Synopsys technology to successfully design and create billions of chips and systems that are found in the electronics that people rely on every single day.

Industry

Computer and computer peripheral equipment and software wholesalers

Company size

10,000+ Employees

Headquarters location

Mountain View, CA, US

Year founded

1986

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