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

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 Β· 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 Β· 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 ...

Senior Machine Learning Engineer

Malvern, PA Β· 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.

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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:

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 Engineer

Philadelphia, PA β€’ On-site

Compunnel
IT ServicesΒ β€’Β 501 - 1,000 employees

Contractor

Re-posted 14 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
β€’ Design, develop, train, test, and deploy machine learning models for enterprise-scale business applications.
β€’ Analyze new and existing datasets to evaluate opportunities for model improvements and enhanced predictive performance.
β€’ Build, compare, and validate multiple machine learning models to determine the most effective production solution.
β€’ Perform feature engineering, model selection, hyperparameter tuning, and model optimization.
β€’ Develop scalable data processing pipelines using Python and PySpark.
β€’ Deploy, monitor, maintain, and improve machine learning models in production environments.
β€’ Assess model performance using appropriate statistical methods and machine learning evaluation metrics.
β€’ Collaborate with business stakeholders and technical teams to identify opportunities for machine learning solutions.
β€’ Conduct exploratory data analysis and provide insights to support data-driven decision-making.
β€’ Work with large-scale datasets within AWS cloud environments.
β€’ Develop reproducible machine learning workflows and maintain technical documentation.
β€’ Troubleshoot production model issues and implement continuous improvements.
β€’ Support experimentation and proof-of-concept initiatives related to machine learning and AI technologies.
β€’ Configure and manage local LLM environments where required to support business use cases.
β€’ Participate in technical discussions, code reviews, and best practice initiatives.
REQUIRED QUALIFICATIONS
β€’ Bachelor's degree in Computer Science, Data Science, Mathematics, Statistics, Engineering, or a related field.
β€’ Minimum 5 years of experience as a Machine Learning Engineer.
β€’ Strong hands-on programming expertise in Python.
β€’ Recent and relevant experience using PySpark for large-scale data processing and machine learning workflows.
β€’ Proven experience developing, training, evaluating, and deploying machine learning models into production environments.
β€’ Experience comparing multiple machine learning algorithms to determine the best-performing production solution.
β€’ Strong understanding of machine learning concepts, including:
- Classification
- Regression
- Clustering
- Ensemble Methods
- Random Forest
- Gradient Boosting
- Feature Engineering
- Model Evaluation
β€’ Experience working with AWS cloud services and machine learning infrastructure.
β€’ Strong data analysis and statistical modeling skills.
β€’ Experience monitoring, maintaining, and improving production machine learning models.
β€’ Experience working with large and complex datasets.
β€’ Knowledge of machine learning lifecycle management and model governance.
β€’ Experience setting up and managing local Large Language Models (LLMs).
β€’ Strong debugging, analytical, and problem-solving skills.
β€’ Ability to independently manage projects and deliver technical solutions.
β€’ Excellent communication and collaboration skills.
PREFERRED QUALIFICATIONS
β€’ Experience with MLOps tools and model monitoring frameworks.
β€’ Experience with machine learning experimentation platforms.
β€’ Familiarity with distributed computing and big data technologies.
β€’ Experience optimizing machine learning workloads in cloud environments.
β€’ Knowledge of advanced machine learning algorithms and predictive analytics techniques.
β€’ Experience within telecommunications, construction workflow management, or enterprise operations environments.
β€’ Exposure to Generative AI technologies in addition to traditional machine learning solutions.
CERTIFICATIONS
β€’ AWS Certified Machine Learning - Specialty (Preferred)
β€’ AWS Certified Solutions Architect - Associate or Professional (Preferred)
β€’ Databricks Machine Learning Certification (Preferred)
β€’ Google Professional Machine Learning Engineer (Preferred)
β€’ 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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