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Senior Machine Learning Engineer Jobs in Huntingdon Valley, PA

Berkadia

Senior Engineer - Machine Learning

Ambler, PA · Hybrid

$100K - $138K/yr

As a Senior Engineer, Machine Learning at Berkadia, you'll be at the forefront of applying cutting-edge machine learning and generative AI to redefine how the commercial real estate industry operates.

RELX

Senior ML Ops Engineer

Philadelphia, PA · On-site

$99K - $137K/yr

As a Senior Machine Learning Ops Engineer, you will bridge Data Science and Engineering to develop AI-based features and ensure the reliability and scalability of machine learning models and services.

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 ...

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All JobsMachine Learning Engineer JobsSenior Machine Learning Engineer JobsSenior Machine Learning Engineer Jobs in Huntingdon Valley, PA

Senior Machine Learning Engineer information

See Huntingdon Valley, PA salary details

$58.4K

$124.1K

$180K

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

As of Sep 3, 2026, the average yearly pay for senior machine learning engineer in Huntingdon Valley, PA is $124,148.00, according to ZipRecruiter salary data. Most workers in this role earn between $102,500.00 and $140,800.00 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 job categories do people searching Senior Machine Learning Engineer jobs in Huntingdon Valley, PA look for?

The top searched job categories for Senior Machine Learning Engineer jobs in Huntingdon Valley, PA are:

What cities near Huntingdon Valley, PA are hiring for Senior Machine Learning Engineer jobs?

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

Senior Machine Learning Engineer jobs near you

Manager, Machine Learning Engineer

Vangard, Inc.

Malvern, PA • On-site

Full-time

Re-posted 18 hours ago

Job description

Core Responsibilities

  • Provides leadership in hiring, coaching, talent development, performance management, and compensation decisions in accordance with Human Resources policies and procedures.

  • Partners with Enterprise, Solution, and Domain Architects to define AI/ML solution architectures and translate strategic initiatives into executable roadmaps, epics, and engineering workstreams.

  • Leads cross-functional delivery across Product, Data Science, Platform, and Engineering teams, driving solutions from concept through production while ensuring alignment to business objectives and enterprise standards.

  • Establishes engineering practices, reusable frameworks, and platform capabilities that improve scalability, consistency, and delivery efficiency across AI/ML initiatives.

  • Oversees the design, implementation, and evolution of data, feature, and model pipelines to support reliable and scalable AI/ML solutions.

  • Applies expertise in machine learning, statistics, optimization, and experimentation methodologies to operationalize predictive and decision-support capabilities.

  • Evaluates data quality, feature readiness, and model inputs in partnership with Data Science teams to support successful model development and deployment.

  • Drives operational excellence through automation, observability, monitoring, incident management, and continuous improvement practices for production AI/ML systems.

  • Ensures adherence to enterprise governance, security, risk, compliance, and model lifecycle management requirements.

  • Engages business and technology stakeholders to understand objectives, assess opportunities, and translate complex requirements into actionable technical solutions.

  • Supports departmental planning, prioritization, and execution of strategic objectives while balancing delivery commitments, operational needs, and organizational goals.

  • Establishes scalable operating models, support processes, and service standards that enable long-term sustainability of AI/ML products and platforms.

  • Communicates technical strategy, solution recommendations, delivery progress, and business impact to senior technology and business leaders.

  • Participates in special projects and performs other duties as assigned.

Qualifications

  • Undergraduate degree or equivalent combination of training and experience. Graduate degree preferred.

  • Minimum of eight years related work experience.

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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