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Machine Learning Engineer Opt Jobs in Philadelphia, PA

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 ...

Vangard, Inc.

Senior AI/ML Engineer

Philadelphia, PA · On-site

$105K - $144K/yr

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

Vangard, Inc.

Senior AI/ML Engineer

Malvern, PA · On-site

$102K - $140K/yr

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

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 ...

Varsity Tutors

Machine Learning Tutor

Trenton, NJ · 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 ...

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

Machine Learning Engineer Opt information

See Philadelphia, PA salary details

$31.8K

$129.9K

$195.3K

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

As of Jun 9, 2026, the average yearly pay for machine learning engineer opt 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 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 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 popular job titles related to Machine Learning Engineer Opt jobs in Philadelphia, PA? For Machine Learning Engineer Opt jobs in Philadelphia, PA, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Opt jobs in Philadelphia, PA look for? The top searched job categories for Machine Learning Engineer Opt jobs in Philadelphia, PA are:
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Machine Learning Engineer Opt jobs near you
Machine Learning Engineer - Document Digitization (LLMs)-Vice President

Machine Learning Engineer - Document Digitization (LLMs)-Vice President

Chase

Wilmington, DE

Other

Medical, Retirement

Posted 3 days ago

JPMorgan Chase & Co. rating

8.1

Company rating: 8.1 out of 10

Based on 468 frontline employees who took The Breakroom Quiz

46th of 141 rated banks

Job description

Machine Learning Engineer – Document Digitization (LLMs)-Vice President

Are you passionate about leveraging advanced technology to solve complex business challenges? As an applied AI/ML, you will have the opportunity to shape the future of document management through cutting-edge AI and machine learning. Join a collaborative team where your expertise will drive impactful solutions and strategic outcomes. This role offers a platform to innovate, lead, and make a difference across the organization.

As a Machine Learning Engineer – Document Digitization (LLMs)-Vice President in our organization, you will design, develop, and deploy secure, scalable, and innovative technology products that transform how documents are processed and managed. You will use advanced AI and machine learning to extract, analyze, and manage information, driving strategic business outcomes. You will collaborate with cross-functional teams, mentor others, and continuously seek opportunities for improvement and innovation.

Job responsibilities

  • Lead the design, development, and integration of AI-powered document digitization solutions, focusing on extracting information and insights from diverse document types.
  • Manage the end-to-end AI/ML lifecycle: model training, validation, deployment, monitoring, and continuous improvement in production environments.
  • Employ generative AI, and large language models (LLMs) to automate and optimize document workflows.
  • Build and maintain scalable document digitization pipelines using Python, AI frameworks, and cloud technologies.
  • Provision and manage cloud resources using infrastructure as code tools (Terraform) and AWS services (SageMaker, Bedrock).
  • Ensure scalability, reliability, security, and compliance of AI/ML solutions, adhering to best practices and governance standards.
  • Collaborate with cross-functional teams to reimagine legacy document processing systems using generative AI and LLMs.
  • Develop and maintain dashboards and reporting tools to monitor digitization accuracy, workflow efficiency, and business impact.
  • Mentor junior engineers and promote best practices in AI/ML, software engineering, and testing.
  • Conduct model validation, human-in-the-loop review, and implement continuous improvement strategies for digitization accuracy.
  • Contribute to communities of practice and explore new and emerging technologies.

Required qualifications, capabilities, and skills

  • Bachelor's or Master's in Computer Science, Data Science, Machine Learning, or related field, with relevant industry experience.
  • Strong proficiency in Python programming; familiarity with Java and front-end technologies (React.JS, AngularJS).
  • Hands-on experience with AI/ML model development, deployment, and MLOps practices in production environments.
  • Expertise in machine learning frameworks (TensorFlow, PyTorch, Scikit-learn, PyTorch Lightning).
  • Knowledge of generative AI models (GANs, VAEs, transformers, diffusion models) and LLMs.
  • Experience with AWS cloud platforms (SageMaker, Bedrock), containerization (Docker, Kubernetes, Amazon EKS), and infrastructure as code (Terraform).
  • Familiarity with NoSQL databases (Mongo Atlas, ElasticSearch, OpenSearch, Neo4J).
  • Experience with agentic coding approaches, autonomous code agents, and last sprinting code generation.
  • Strong understanding of SDLC, CI/CD, resiliency, and security practices.
  • Demonstrated ability to accelerate development using AI technologies.
  • Experience deploying and maintaining AI/ML solutions in large-scale, production environments. and strong problem-solving, communication, and collaboration skills.

Preferred qualifications, capabilities, and skills

  • Experience in financial services, especially investment banking or credit risk operations
  • Expertise in agentic AI frameworks, prompt optimization, and fine-tuning SLMs
  • Familiarity with distributed computing, data sharing, and DDP training
  • Experience in design/code reviews and mentoring teams
  • AWS Generative AI Developer Professional certification or equivalent
About Us

JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans

About the Team

Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.

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