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Machine Learning Engineer Jobs in Philadelphia, PA

JOB SUMMARY We are seeking a hands-on Machine Learning Engineer to design, build, evaluate, deploy, and maintain machine learning models in production environments. The ideal candidate will have ...

Senior Machine Learning Engineer

Malvern, PA · On-site

$120K - $158K/yr

We are assisting our client in hiring for a Senior Machine Learning Engineer. Our client is an established SaaS company serving banks, credit unions, and fintechs. Their cloud-based platform helps ...

Senior Machine Learning Engineer

Malvern, PA · On-site

$102K - $140K/yr

This role partners closely with quantitative researchers, data scientists, and investment teams to engineer, deploy, and operate production-grade machine learning models that drive research ...

New

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.

We are currently seeking a Senior Machine Learning Engineer to join our team in Moorestown, NJ. Responsibilities: * Develops, researches, and applies machine learning, deep learning, visual ...

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Machine Learning Engineer information

See Philadelphia, PA salary details

$31.8K

$129.9K

$195.3K

How much do machine learning engineer jobs pay per year?

As of Sep 12, 2026, the average yearly pay for machine learning engineer in Philadelphia, PA is $129,939.00, according to ZipRecruiter salary data. Most workers in this role earn between $102,400.00 and $156,400.00 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 and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What does a machine learning engineer do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

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 strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

What are some common challenges faced by machine learning engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate 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 Philadelphia, PA?

The most popular types of Machine Learning Engineer jobs in Philadelphia, PA are:

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

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

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

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

Infographic showing various Machine Learning Engineer job openings in Philadelphia, PA as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 75% Full Time, 21% Part Time, and 2% Contract. Highlights an 85% Physical, 2% Hybrid, and 13% Remote job distribution, with an average salary of $129,939 per year, or $62.5 per hour.

Machine Learning Engineer

Philadelphia, PA • On-site

Compunnel
IT Services • 501 - 1,000 employees

Contractor

Re-posted 11 days ago


Job description

JOB SUMMARY
We are seeking a hands-on Machine Learning Engineer to design, build, evaluate, deploy, and maintain machine learning models in production environments. The ideal candidate will have strong expertise in Python, PySpark, AWS, and machine learning model development, with a proven track record of delivering production-ready models that drive business outcomes. This role requires a highly technical individual contributor who can analyze data, compare model performance, optimize solutions, and manage the complete machine learning lifecycle. Experience with local LLM deployments is required, but the primary focus of this role is traditional machine learning model development and production deployment.
KEY RESPONSIBILITIES
• Design, develop, train, test, and deploy machine learning models for enterprise-scale business applications.
• Analyze new and existing datasets to evaluate opportunities for model improvements and enhanced predictive performance.
• Build, compare, and validate multiple machine learning models to determine the most effective production solution.
• Perform feature engineering, model selection, hyperparameter tuning, and model optimization.
• Develop scalable data processing pipelines using Python and PySpark.
• Deploy, monitor, maintain, and improve machine learning models in production environments.
• Assess model performance using appropriate statistical methods and machine learning evaluation metrics.
• Collaborate with business stakeholders and technical teams to identify opportunities for machine learning solutions.
• Conduct exploratory data analysis and provide insights to support data-driven decision-making.
• Work with large-scale datasets within AWS cloud environments.
• Develop reproducible machine learning workflows and maintain technical documentation.
• Troubleshoot production model issues and implement continuous improvements.
• Support experimentation and proof-of-concept initiatives related to machine learning and AI technologies.
• Configure and manage local LLM environments where required to support business use cases.
• Participate in technical discussions, code reviews, and best practice initiatives.
REQUIRED QUALIFICATIONS
• Bachelor's degree in Computer Science, Data Science, Mathematics, Statistics, Engineering, or a related field.
• Minimum 5 years of experience as a Machine Learning Engineer.
• Strong hands-on programming expertise in Python.
• Recent and relevant experience using PySpark for large-scale data processing and machine learning workflows.
• Proven experience developing, training, evaluating, and deploying machine learning models into production environments.
• Experience comparing multiple machine learning algorithms to determine the best-performing production solution.
• Strong understanding of machine learning concepts, including:
- Classification
- Regression
- Clustering
- Ensemble Methods
- Random Forest
- Gradient Boosting
- Feature Engineering
- Model Evaluation
• Experience working with AWS cloud services and machine learning infrastructure.
• Strong data analysis and statistical modeling skills.
• Experience monitoring, maintaining, and improving production machine learning models.
• Experience working with large and complex datasets.
• Knowledge of machine learning lifecycle management and model governance.
• Experience setting up and managing local Large Language Models (LLMs).
• Strong debugging, analytical, and problem-solving skills.
• Ability to independently manage projects and deliver technical solutions.
• Excellent communication and collaboration skills.
PREFERRED QUALIFICATIONS
• Experience with MLOps tools and model monitoring frameworks.
• Experience with machine learning experimentation platforms.
• Familiarity with distributed computing and big data technologies.
• Experience optimizing machine learning workloads in cloud environments.
• Knowledge of advanced machine learning algorithms and predictive analytics techniques.
• Experience within telecommunications, construction workflow management, or enterprise operations environments.
• Exposure to Generative AI technologies in addition to traditional machine learning solutions.
CERTIFICATIONS
• AWS Certified Machine Learning - Specialty (Preferred)
• AWS Certified Solutions Architect - Associate or Professional (Preferred)
• Databricks Machine Learning Certification (Preferred)
• Google Professional Machine Learning Engineer (Preferred)
• Relevant Python, Data Science, or Machine Learning Certifications (Preferred)

Compunnel logo

About Compunnel

Sourced by ZipRecruiter

Compunnel is a well-known company located in Plainsboro, NJ, US, recognized in the industry of IT Services and Solutions. Established in 1989, Compunnel offers a suite of services that help businesses integrate technology efficiently into their operations, a recognizable name in the IT solutions sphere for over three decades. The company’s service portfolio includes Digital Transformation, Business Intelligence, Cloud Services, Cybersecurity, and Application Modern Services, among others. Guided by its mission "to innovate with industry-leading digital solutions and disruptive tech strategies for unimagining business growth," the company underlines its commitment to offering out-of-the-box solutions to its clients. Remarkable achievements of the company include serving more than 30 Fortune 500 companies and providing job opportunities for over 50,000 individuals.

Industry

It services

Company size

501 - 1,000 Employees

Headquarters location

Plainsboro, NJ, US

Year founded

1994

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