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Research Assistant Machine Learning Jobs in Philadelphia, PA

Bespoke Labs

Machine Learning Engineer

Trenton, NJ · On-site

Read eval signal and training curves to determine whether a change actually helped, and feed findings back to the research and environment teams * Integrate RL environments into the training stack ...

Bespoke Labs

Machine Learning Engineer

Trenton, NJ · On-site

Read eval signal and training curves to determine whether a change actually helped, and feed findings back to the research and environment teams * Integrate RL environments into the training stack ...

Bespoke Labs

Machine Learning Engineer

Wilmington, DE · On-site

Read eval signal and training curves to determine whether a change actually helped, and feed findings back to the research and environment teams * Integrate RL environments into the training stack ...

Bespoke Labs

Machine Learning Engineer

Wilmington, DE · On-site

Read eval signal and training curves to determine whether a change actually helped, and feed findings back to the research and environment teams * Integrate RL environments into the training stack ...

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All JobsResearch Machine Learning JobsResearch Assistant Machine Learning JobsResearch Assistant Machine Learning Jobs in Philadelphia, PA

Research Assistant Machine Learning information

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How much do research assistant machine learning jobs pay per hour?

As of Sep 7, 2026, the average hourly pay for research assistant machine learning in Philadelphia, PA is $22.11, according to ZipRecruiter salary data. Most workers in this role earn between $18.65 and $25.72 per hour, depending on experience, location, and employer.

What is a research assistant machine learning?

A Research Assistant in Machine Learning supports research projects by implementing algorithms, analyzing data, and conducting experiments to advance AI models. They assist senior researchers by preprocessing datasets, developing machine learning models, and evaluating their performance. Responsibilities may also include coding, literature reviews, and writing research papers. This role is typically found in academia, research labs, or industry R&D teams. Strong programming skills, statistical knowledge, and familiarity with ML frameworks like TensorFlow or PyTorch are essential.

What types of projects might a research assistant machine learning typically work on?

As a Research Assistant in Machine Learning, you may be involved in projects such as developing and evaluating predictive models, processing and analyzing large datasets, and assisting in the publication of research findings. Your work could contribute to applications like natural language processing, computer vision, or recommendation systems, depending on the focus of the research group. You’ll often collaborate closely with senior researchers, data scientists, or PhD students, allowing you to participate in brainstorming sessions, code development, and experimental design. This experience provides valuable exposure to cutting-edge technology and can serve as a strong foundation for a research or industry career in machine learning.

What are the key skills and qualifications needed to thrive as a research assistant machine learning?

To thrive as a Research Assistant Machine Learning, you need a solid understanding of machine learning algorithms, programming skills (especially in Python or R), and a background in statistics or computer science, often supported by a bachelor’s or master’s degree. Experience with frameworks such as TensorFlow, PyTorch, and data analysis tools, as well as familiarity with version control systems like Git, is highly beneficial. Strong problem-solving abilities, attention to detail, and effective communication skills help you excel in collaborative research environments. These skills ensure you can contribute meaningfully to research projects, analyze complex datasets, and communicate findings effectively within interdisciplinary teams.

What are popular job titles related to Research Assistant Machine Learning jobs in Philadelphia, PA?

For Research Assistant Machine Learning jobs in Philadelphia, PA, the most frequently searched job titles are:

What job categories do people searching Research Assistant Machine Learning jobs in Philadelphia, PA look for?

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What cities near Philadelphia, PA are hiring for Research Assistant Machine Learning jobs?

Cities near Philadelphia, PA with the most Research Assistant Machine Learning job openings:

Research Assistant Machine Learning jobs near you
Infographic showing various Research Assistant Machine Learning job openings in Philadelphia, PA as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 23% Part Time, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $45,985 per year, or $22.1 per hour.

Machine Learning/AI Engineering Manager

Vangard, Inc.

Malvern, PA • On-site

Full-time

Posted 2 days ago

New

Job description

We are seeking a Machine Learning Engineering Manager to lead a high-performing team of Machine Learning Engineers responsible for building, operating, and evolving Vanguard's production AI, ML, and Generative AI solutions.

This leader will oversee engineering for a portfolio of traditional machine learning and GenAI capabilities that power investor personalization, financial planning, and advice experiences across Personal Wealth Technology. You will partner closely with Data Scientists, Product Owners, Architects, and Vanguard's Investment Strategy Group (ISG) methodology teams to transform sophisticated models and research into reliable, scalable, and trusted production solutions.

This is a highly technical leadership role. The successful candidate will be expected to actively participate in solution architecture, technical design, engineering strategy, model operations, production support, and Agile delivery while developing the next generation of AI engineering talent.

Responsibilities

  • Lead a team of Machine Learning Engineers delivering scalable, secure, reliable, and extensible AI solutions
  • Develop, maintain, support, and evolve a portfolio of production machine learning and generative AI models
  • Partner with Investment Strategy Group methodology teams to operationalize financial advice, portfolio construction, and personalization models
  • Ensure production readiness through monitoring, alerting, validation, testing, observability, and incident management practices
  • Drive engineering excellence, DevOps, MLOps, LLMOps, and FinOps disciplines
  • Shape AI and ML roadmaps alongside Data Scientists, Product Owners, and stakeholders
  • Provide technical direction and architectural guidance for complex AI and ML initiatives
  • Build trusted relationships across technology and business teams to influence strategy and delivery outcomes
  • Establish standards and best practices that enable safe, trustworthy, explainable, and scalable AI solutions
  • Drive adoption of GenAI and agentic solutions within the engineering organization to improve efficiency, automation, and delivery quality
  • Hire, coach, mentor, and develop future technical leaders

What You'll Own

  • Delivery, operation, and continuous improvement of Vanguard's production AI, ML, and GenAI platforms and solutions
  • Engineering ownership along with ISG Methodology for the Vanguard Financial Advice Model (VFAM) and Risk-Based Research Engine (RBRE)
  • Model health monitoring, observability, availability, and operational excellence across all production models
  • Reliability and support processes ensuring production AI systems remain resilient, trusted, and available
  • Technical leadership for Machine Learning Engineering, MLOps, LLMOps, DevOps, and FinOps practices
  • Team leadership, coaching, and development for a high-performing Machine Learning Engineering organization
  • Stakeholder relationships across Technology, Methodology, Product, and Analytics teams

Qualifications

  • Minimum of eight years data analytics, programming, database administration, or data management experience.
  • Undergraduate degree or equivalent combination of training and experience. Graduate degree preferred.

Preferred Qualifications

  • Proven experience leading Machine Learning, AI Engineering, or Software Engineering teams
  • Strong technical depth in production AI/ML systems and cloud-native engineering
  • Experience establishing operational excellence for production AI platforms
  • Demonstrated success partnering with product, analytics, and business stakeholders
  • Passion for developing engineering talent and building high-performing teams
  • Ability to balance strategic leadership with hands-on technical engagement
  • Interest in advancing modern engineering practices, including MLOps, LLMOps, FinOps, and agentic AI

Why This Role

  • Directly influence how Vanguard delivers personalized financial advice at scale
  • Lead engineering for some of Vanguard's most strategic AI and machine learning capabilities
  • Work at the intersection of financial methodology, applied AI, and large-scale engineering
  • Shape the future of GenAI, agentic systems, and AI engineering practices within Personal Wealth Technology
  • Develop a talented team while driving meaningful outcomes for millions of investors
  • Join a leadership team committed to innovation, engineering excellence, and investor-centric 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.

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