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Senior Machine Learning Engineer Jobs in Springfield, PA

Machine Learning Tutor

Chester, 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 ...

We are seeking a creative, and curious Senior Data Science Software Engineer to join our team. In ... Lead the end-to-end development of machine learning and data products aligned to business ...

HCL Global Systems Inc is a technology company specializing in AI and machine learning solutions. They are seeking an AI/ML Engineer to implement agentic frameworks, develop generative AI ...

Lead Data Scientist

Philadelphia, PA · On-site

$150K - $175K/yr

The Sr. Director will apply scientific methods to identify business optimization strategies and ... Work with machine learning engineers, data engineers, DevOps and software developers to deploy ...

The Sr. Director will apply scientific methods to identify business optimization strategies and ... Work with machine learning engineers, data engineers, DevOps and software developers to deploy ...

The Sr. Director will apply scientific methods to identify business optimization strategies and ... Work with machine learning engineers, data engineers, DevOps and software developers to deploy ...

Showing results 41-60

Senior Machine Learning Engineer information

See Springfield, PA salary details

$56.1K

$119.4K

$173.1K

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

As of Aug 22, 2026, the average yearly pay for senior machine learning engineer in Springfield, PA is $119,388.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,600.00 and $135,400.00 per year, depending on experience, location, and employer.

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 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 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 cities near Springfield, PA are hiring for Senior Machine Learning Engineer jobs?

Cities near Springfield, PA with the most Senior Machine Learning Engineer job openings:

Infographic showing various Senior Machine Learning Engineer job openings in Springfield, PA as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 23% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $119,388 per year, or $57.4 per hour.

Machine Learning Internship - PhD: 2027 - Susquehanna International Group

Susquehanna International Group

Bala Cynwyd, PA • On-site

Full-time

Posted 29 days ago


Job description

Overview
Our Machine Learning PhD Internship is a 10-week immersive experience designed for PhD candidates who are passionate about solving high-impact problems at the intersection of data, algorithms, and markets.
As a Machine Learning Intern at Susquehanna, you'll work on high-impact projects that closely reflect the challenges and workflows of our full-time research team. You'll apply your technical expertise in machine learning and data science to real-world financial problems, while developing a deep understanding of how machine learning integrates into Susquehanna's research and trading systems. You will leverage vast and diverse datasets and apply cutting-edge machine learning at scale to drive data-informed decisions in predictive modeling to strategic execution.
What You Can Expect

  • Conduct research and develop ML models to identify patterns in noisy, non-stationary data
  • Work side-by-side with our Machine Learning team on real, impactful problems in quantitative trading and finance, bridging the gap between cutting-edge ML research and practical implementation
  • Collaborate with researchers, developers, and traders to improve existing models and explore new algorithmic approaches
  • Design and run experiments using the latest ML tools and frameworks
  • One-on-one mentorship from experienced researchers and technologists
  • Participate in a comprehensive education program with deep dives into Susquehanna's ML, quant, and trading practices
  • Apply rigorous scientific methods to extract signals from complex datasets and shape our understanding of market behavior
  • Explore various aspects of machine learning in quantitative finance from alpha generation and signal processing to model deployment and risk-aware decision making

What we're looking for
  • Currently pursuing a PhD in Computer Science, Machine Learning, Statistics, Physics, Applied Mathematics, or a closely related field
  • Proven experience applying machine learning techniques in a professional or academic setting
  • Strong publication record in top-tier conferences such as NeurIPS, ICML, or ICLR
  • Hands-on experience with machine learning frameworks, including PyTorch and TensorFlow
  • Deep interest in solving complex problems and a drive to innovate in a fast-paced, competitive environment

Why Join Us?
  • Work with a world-class team of researchers and technologists
  • Access to unparalleled financial data and computing resources
  • Opportunity to make a direct impact on trading performance
  • Collaborative, intellectually stimulating environment with global reach

About Susquehanna
Susquehanna is a global quantitative trading firm powered by scientific rigor, curiosity, and innovation. Our culture is intellectually driven and highly collaborative, bringing together researchers, engineers, and traders to design and deploy impactful strategies in our systematic trading environment. To meet the unique challenges of global markets, Susquehanna applies machine learning and advanced quantitative research to vast datasets in order to uncover actionable insights and build effective strategies. By uniting deep market expertise with cutting-edge technology, we excel in solving complex problems and pushing boundaries together.
If you're a recruiting agency and want to partner with us, please reach out to recruiting@sig.com. Any resume or referral submitted in the absence of a signed agreement will not be eligible for an agency fee.