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Senior Machine Learning Engineer Jobs in Pennsylvania

Vanguard Group

Senior Machine Learning Engineer

Malvern, PA · 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.

New

Vangard, Inc.

Senior Machine Learning Engineer

Malvern, PA

$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.

New

Air

Senior Machine Learning Engineer

Pittsburgh, PA · On-site

$118K - $156K/yr

... engineers Qualifications * U.S. Citizenship is required * Advanced degree, or bachelor's with at least 3 years of experience, in Data Science, Machine Learning or a related field Required Skills:

Air

Senior Machine Learning Engineer

Pittsburgh, PA

$118K - $156K/yr

... engineers Qualifications * U.S. Citizenship is required * Advanced degree, or bachelor's with at least 3 years of experience, in Data Science, Machine Learning or a related field Required Skills:

Compunnel

Machine Learning Engineer

Philadelphia, PA · On-site

JOB SUMMARY Seeking a hands-on Machine Learning Engineer with strong Python programming expertise and recent PySpark experience to build, deploy, and support production-ready machine learning ...

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Senior Machine Learning Engineer information

See Pennsylvania salary details

$59.6K

$126.9K

$183.9K

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

As of Jul 20, 2026, the average yearly pay for senior machine learning engineer in Pennsylvania is $126,861.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,800.00 and $143,800.00 per year, depending on experience, location, and employer.

What are some common challenges Senior Machine Learning Engineers face when deploying models to production, and how can they be addressed?

Senior Machine Learning Engineers often encounter challenges related to model scalability, maintaining performance in real-world scenarios, and ensuring reliable integration with existing systems. Addressing these challenges typically involves thorough testing, implementing robust monitoring for model drift, and collaborating closely with DevOps and software engineering teams to streamline deployment pipelines. Staying updated on best practices in MLOps and adopting tools for automated deployment and monitoring can greatly improve the reliability and efficiency of production models.

What does a Senior Machine Learning Engineer do?

A Senior Machine Learning Engineer designs, develops, and implements machine learning models to solve complex problems. They are responsible for selecting appropriate algorithms, preprocessing data, and optimizing model performance. Additionally, they collaborate with data scientists, software engineers, and product teams to integrate machine learning solutions into production systems. Senior engineers also mentor junior team members and contribute to setting technical direction for machine learning projects.

What are the key skills and qualifications needed to thrive as a Senior Machine Learning Engineer, and why are they important?

To thrive as a Senior Machine Learning Engineer, you need advanced knowledge of machine learning algorithms, statistical modeling, and programming languages like Python or Java, typically supported by a degree in computer science or a related field. Experience with frameworks and tools such as TensorFlow, PyTorch, scikit-learn, and cloud platforms, as well as familiarity with version control and CI/CD systems, is essential. Strong problem-solving, communication, and leadership skills help you collaborate effectively and mentor junior team members. These capabilities are crucial for designing scalable ML solutions and driving impactful results within complex, dynamic projects.

What is the difference between Senior Machine Learning Engineer vs Data Scientist?

AspectSenior Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience with ML frameworksBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops and deploys ML models in production systemsAnalyzes data, builds models, and provides insights
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, tech

While both roles require strong technical skills and knowledge of machine learning, Senior Machine Learning Engineers focus more on deploying scalable ML solutions in production environments, whereas Data Scientists primarily analyze data and develop models for insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Machine Learning Engineer jobs in Pennsylvania? The most popular types of Machine Learning Engineer jobs in Pennsylvania are:
What are popular job titles related to Senior Machine Learning Engineer jobs in Pennsylvania? For Senior Machine Learning Engineer jobs in Pennsylvania, the most frequently searched job titles are:
What job categories do people searching Senior Machine Learning Engineer jobs in Pennsylvania look for? The top searched job categories for Senior Machine Learning Engineer jobs in Pennsylvania are:
What cities in Pennsylvania are hiring for Senior Machine Learning Engineer jobs? Cities in Pennsylvania with the most Senior Machine Learning Engineer job openings:
Senior Machine Learning Engineer jobs near you
Infographic showing various Senior Machine Learning Engineer job openings in Pennsylvania as of July 2026, with employment types broken down into 85% Full Time, 9% Part Time, 1% Temporary, 4% Contract, and 1% Nights. Highlights an 85% Physical, 7% Hybrid, and 8% Remote job distribution, with an average salary of $126,861 per year, or $61 per hour.
Senior Machine Learning Engineer

Senior Machine Learning Engineer

Vanguard Group

Malvern, PA • On-site

$102K - $140K/yr

Full-time

Posted 3 days ago

New

Vanguard rating

8.7

Company rating: 8.7 out of 10

Based on 62 frontline employees who took The Breakroom Quiz

17th of 148 rated financial services

Job description

Core Responsibilities
  • 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.
  • Develop and maintain feature engineering, feature storage, and data preparation pipelines.
  • Automate model deployment, testing, validation, and release processes using CI/CD practices.
  • Build batch, real-time, and event-driven architectures.
  • Implement model monitoring for performance, drift detection, data quality, and operational health.
  • Partner with quantitative researchers and data scientists to productionalize research models.
  • Manage model versioning, lineage tracking, experiment management, and reproducibility.
  • Optimize model performance, scalability, reliability, and cloud cost efficiency.
  • Establish engineering standards, testing frameworks, and governance controls for ML solutions.
  • Support production operations, incident response, and continuous improvement of deployed models.

Required Qualifications:
  • Minimum of eight years related work experience, with at least three years of development experience.
  • Undergraduate degree or equivalent combination of training and experience. Graduate degree preferred.
  • Experience in software engineering, machine learning engineering, data engineering, or a related technical discipline.
  • Strong experience building and deploying machine learning solutions in production environments.
  • Expertise in Python and modern data science libraries (Pandas, NumPy, Scikit-Learn, PyTorch, TensorFlow, or similar).
  • Hands-on experience with AWS services, including SageMaker
  • Experience building and maintaining machine learning pipelines, feature engineering workflows, and model deployment processes.
  • Knowledge of MLOps practices, including CI/CD, model versioning, experiment tracking, monitoring, and automated retraining.
  • Strong understanding of software development lifecycle practices, testing strategies, and production support.
  • Ability to work effectively with researchers, data scientists, and business stakeholders to deliver business outcomes.

Special Factors
Sponsorship
Vanguard is not offering visa sponsorship for this position.
About Vanguard
At Vanguard, we don't just have a mission-we're on a mission.
To work for the long-term financial wellbeing of our clients. To lead through product and services that transform our clients' lives. To learn and develop our skills as individuals and as a team. From Malvern to Melbourne, our mission drives us forward and inspires us to be our best.
How We Work
Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.

What Vanguard employees say

Pay

Benefits

Hours and flexibility

Workplace

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