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

As a Machine Learning Engineer, you will prepare datasets, train and optimize models, and maintain and improve model inference services. You will learn and apply new techniques from open source ...

Comscore, Total Visits, March 2025) Day to Day As a Machine Learning Engineer III you will be a team lead on the Marketplace Efficiency - Job Reach team. Your team will be responsible for maintaining ...

Comscore, Total Visits, March 2025) Day to Day As a Machine Learning Engineer III, you will be a team lead. You will own one of the team's major workstreams, help drive technical direction for the ...

Machine Learning Engineer

Philadelphia, PA · On-site

$115.50K - $138.70K/yr

Title: ML Engineer Location: Philadelphia, PA - Onsite 4years of experience in Machine Learning, NLP, NLU, Deep Learning, building ML pipelines and data engineering * * * AI Platforms: DataRobot ...

Machine Learning Engineer, Specialist

Malvern, PA · On-site

$112.40K - $134.90K/yr

Demonstrate an excellent understanding of the machine learning development lifecycle, including data engineering, exploratory data analysis, modeling, and ML implementation and operations. * Design ...

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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 May 28, 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 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 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 Machine Learning Engineers?

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 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 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 May 2026, with employment types broken down into 84% Full Time, 10% Part Time, 3% Temporary, and 3% Contract. Highlights an 98% Physical, 1% Hybrid, and 1% Remote job distribution, with an average salary of $124,281 per year, or $59.8 per hour.
Machine Learning Engineer

Machine Learning Engineer

Children's Hospital of Philadelphia

Philadelphia, PA • On-site

Other

This job post has expired 1 day ago. Applications are no longer accepted.


Children's Hospital Of Philadelphia rating

8.3

Company rating: 8.3 out of 10

Based on 94 frontline employees who took The Breakroom Quiz

75th of 989 rated hospitals


Job description

SHIFT:

Day (United States of America)

Seeking Breakthrough Makers
Children's Hospital of Philadelphia (CHOP) offers countless ways to change lives. Our diverse community of more than 20,000 Breakthrough Makers will inspire you to pursue passions, develop expertise, and drive innovation.
At CHOP, your experience is valued; your voice is heard; and your contributions make a difference for patients and families. Join us as we build on our promise to advance pediatric care-and your career.
CHOP's Commitment to Diversity, Equity, and Inclusion
CHOP is committed to building an inclusive culture where employees feel a sense of belonging, connection, and community within their workplace. We are a team dedicated to fostering an environment that allows for all to be their authentic selves. We are focused on attracting, cultivating, and retaining diverse talent who can help us deliver on our mission to be a world leader in the advancement of healthcare for children.
We strongly encourage all candidates of diverse backgrounds and lived experiences to apply.
A Brief Overview

The Campbell Laboratory at the Children's Hospital of Philadelphia is seeking a Machine Learning Engineer to help advance our mission to diagnose rare genetic diseases more quickly and accurately. We develop and train large language models (LLMs) to better understand clinical data from the electronic health record (EHR) and to identify ways to facilitate accurate, equitable diagnoses for every child-especially those from historically marginalized backgrounds.

As a Machine Learning Engineer, you will work closely with data scientists, clinicians, and other researchers to design, implement, and scale state-of-the-art machine learning workflows. You will utilize our on-premises GPU/SLURM cluster and cloud-based TPU instances (Google Cloud) to train and deploy LLMs using Hugging Face Transformers, PyTorch, and JAX. This role combines robust software engineering practices with advanced machine learning and natural language processing (NLP) techniques, with a focus on reproducibility and high-quality code.

Our innovative and interdisciplinary environment values diversity, fosters professional growth, and drives impactful research that benefits children worldwide. If you are passionate about building robust machine learning systems, enjoy working on high-impact problems, and thrive in a collaborative research environment, we encourage you to apply.


What you will do

  • Configure and utilize on-premises SLURM cluster with GPU resources to ensure efficient and reliable job scheduling for large-scale model training.

  • Manage and optimize cloud-based infrastructures (e.g., TPU Pods on Google Cloud) for distributed model training and evaluation.

  • Collaborate with data scientists to implement and fine-tune LLMs (e.g., Transformer architectures in PyTorch, TensorFlow, or JAX) for clinical and biomedical NLP tasks.

  • Develop efficient training pipelines, including data loading, preprocessing, feature extraction, and model deployment.

  • Evaluate model performance and optimize hyperparameters, GPU/TPU utilization, and distributed training strategies.

  • Collaborate cross-functionally with clinicians, data scientists, analysts, and IT teams to support and enhance machine learning operations (MLOps).

  • Work with relational databases (e.g., Snowflake, BigQuery, Oracle SQL, MySQL) and distributed storage systems to access and manage EHR data.

  • Partner with data scientists and domain experts to design data pipelines that integrate with existing hospital systems.

  • Write clean, well-documented, and maintainable code following best practices

  • Contribute to shared code repositories using Git, ensuring reproducibility and version control for collaborative projects.

  • Develop CI/CD workflows to automate model testing, containerization, and deployment to production environments.

  • Monitor deployed models for performance drift, latency, and reliability, and implement automated alerts and feedback loops to refine model behavior.

  • Produce clear technical documentation, including system architecture diagrams, training procedures, and user guides for internal stakeholders.

  • Present engineering best practices, findings, and process updates to clinicians, researchers, and other non-technical audiences as needed.

Education Qualifications

  • Bachelor's Degree Required

  • Bachelor's Degree Analytics, Data Science, Statistics, Mathematics, Computer Science or a related field Preferred

  • Masters or PhD in Analytics, Data Science, Statistics, Mathematics, Computer Science or a related field Preferred

Experience Qualifications

  • At least three (3) years experience with progressively more complex data science, applied statistics, machine learning, or mathematical modeling projects. Required
  • At least four (4) years with progressively more complex data science, applied statistics, machine learning, or mathematical modeling projects Preferred
  • At least one year of experience with complex data science, applied statistics, machine learning, or mathematical modeling projects Preferred
  • Natural language processing experience, particularly in the biological and medical domains Preferred
  • Experience with transformer architecture and associated software (e.g., PyTorch, Tensorflow, JAX) is Preferred
  • Experience using distributed computing technologies Preferred
  • Experience with cloud virtual machine environments Preferred
  • Experience implementing distributed training on GPUs or TPUs in cloud platforms (e.g., Google Cloud, AWS, Azure).
  • Experience with prompt engineering, semantic search, or retrieval-augmented generation (RAG) in a research or production environment.
  • Familiarity with MLOps pipelines (CI/CD, containerization, monitoring, and logging frameworks).
  • Exposure to healthcare or biomedical data and associated privacy/security regulations (e.g., HIPAA) is a plus.
  • Experience with advanced NLP techniques or LLMs in a research or production environment.

Skills and Abilities

  • Proven software engineering experience, including structured development methods, testing, and version control.
  • Hands-on experience with Python and at least one deep learning framework (e.g., PyTorch, TensorFlow, or JAX).
  • Familiarity with relational databases (e.g., Snowflake, BigQuery, Oracle SQL, MySQL).
  • Experience with Linux/Unix environments, shell scripting, and cluster computing systems (e.g., SLURM).


To carry out its mission, CHOP is committed to supporting the health of our patients, families, workforce, and global community. As a condition of employment, CHOP employees who work in patient care buildings or who have patient facing responsibilities must be fully vaccinated against COVID-19 and receive an annual influenza vaccine. Learn more.
Employees may request exemptions for valid religious and medical reasons. Start dates may be delayed until candidates are immunized or exemption requests are reviewed.
EEO / VEVRAA Federal Contractor | Tobacco Statement

SALARY RANGE:

$104,600.00 - $138,600.00 Annually

Salary ranges are shown for full-time jobs. If you're working part-time, your pay will be adjusted accordingly.

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At CHOP, we are committed to fair and transparent pay practices. Factors such as skills and experience could result in an offer above the salary range noted in this job posting. Click here for more information regarding CHOP's Compensation and Benefits.


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About Children's Hospital of Philadelphia

Sourced by ZipRecruiter

The Children's Hospital of Philadelphia (CHOP) is a renowned healthcare institution dedicated to the welfare of children. Established in 1855 and situated in the heart of Philadelphia, PA, US, it's known primarily for pediatric healthcare services, pioneering new treatments, and conducting notable research in child-related medical disciplines. As an industry trailblazer, CHOP has a well-established reputation in the pediatric healthcare sector and is recognized globally for its innovative approach towards advancing children's healthcare.

Industry

Hospitals

Company size

10,000+ Employees

Headquarters location

Philadelphia, PA, US

Year founded

1855