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Machine Learning Engineer Opt Jobs in Exton, PA (NOW HIRING)

RIT Solutions, Inc.

Data Engineer

Malvern, PA · On-site

$112K - $134K/yr

Responsibilities : • We are seeking an experienced Machine Learning Engineer to join our AI/ML Engineering team. You will be responsible for developing and optimizing complex data pipelines ...

Varsity Tutors

Machine Learning Tutor

Chester, PA · Remote

$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 ...

Elsevier

Senior ML Ops Engineer

Philadelphia, PA · On-site

$99K - $137K/yr

In this role, the Senior Machine Learning Engineer will bridge Data Science and Engineering to develop AI-based features and ensure the deployment of secure, reliable, and scalable machine learning ...

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All JobsMachine Learning Engineer Opt JobsMachine Learning Engineer Opt Jobs in Exton, PA

Machine Learning Engineer Opt information

See Exton, PA salary details

$30.4K

$124.3K

$186.8K

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

As of Sep 14, 2026, the average yearly pay for machine learning engineer opt in Exton, PA is $124,281.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,000.00 and $149,600.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models into production environments. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, reliable systems that organizations can use to make predictions or automate tasks. Their responsibilities include data preprocessing, choosing appropriate algorithms, model training, and ensuring the model's performance in real-world applications. Machine Learning Engineers often collaborate with data scientists, data engineers, and product teams to deliver intelligent solutions.

What are some common challenges machine learning engineers face when deploying models to production environments?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, handling data drift, and integrating models seamlessly with existing systems when deploying to production. Monitoring model performance in real time and retraining models as new data becomes available are also critical tasks. Collaboration with data engineers and DevOps teams is essential to address infrastructure and deployment hurdles while maintaining model accuracy and reliability.

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 a solid background in mathematics, statistics, and programming (especially Python), typically supported by a degree in computer science, engineering, or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch), data processing tools, and cloud platforms, along with relevant certifications, is highly valuable. Strong problem-solving ability, collaboration, and effective communication are standout soft skills in this role. These skills and qualities ensure the successful development, deployment, and integration of machine learning solutions that drive business value.

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

AspectMachine Learning Engineer OptData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; certifications in ML toolsBachelor's or Master's in CS, Statistics, or related fields; data analysis certifications
Work EnvironmentDevelops, tests, and deploys ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, AI startups, e-commerce, financeResearch institutions, tech firms, consulting, finance
Common Search & ComparisonOften compared for technical skills and deployment focusCompared for data analysis and business insights

Machine Learning Engineers Opt focus on deploying scalable ML models in production environments, while Data Scientists primarily analyze data and develop models for insights. Both roles require strong technical skills, but their core responsibilities differ in application and deployment.

What job categories do people searching Machine Learning Engineer Opt jobs in Exton, PA look for?

The top searched job categories for Machine Learning Engineer Opt jobs in Exton, PA are:

What cities near Exton, PA are hiring for Machine Learning Engineer Opt jobs?

Cities near Exton, PA with the most Machine Learning Engineer Opt job openings:

Machine Learning Engineer Opt jobs near you
Infographic showing various Machine Learning Engineer Opt job openings in Exton, PA as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 71% Full Time, 25% Part Time, and 2% Contract. Highlights an 82% Physical, 2% Hybrid, and 16% Remote job distribution, with an average salary of $124,281 per year, or $59.8 per hour.

Machine Learning/AI Engineering Manager

Malvern, PA

Vanguard
Photography Services • 1 - 5K employees
Learn more about Vanguardexternal

Full-time

Posted 10 days ago

Job description

​Applying AI Engineering to Improve the Lives of Investors Advice is the fullest manifestation of Vanguard's mission. Our goal is to deliver high-quality, trusted, and personalized financial advice at scale. Achieving that vision requires world-class Data & AI Engineering capabilities that transform advanced analytics, machine learning, and generative AI into production solutions used by advisors, clients, and business partners every day. Within Personal Wealth Technology (PWT), we are building and operating the next generation of AI-powered capabilities that drive personalized financial advice, portfolio construction, and investor outcomes. This is a unique opportunity to lead the engineering team responsible for some of Vanguard's most critical AI and machine learning platforms and products.

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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