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Machine Learning Engineer Jobs in Philadelphia, PA

AI / Machine Learning Engineer (Contract) Location: Philadelphia, PA or Charlotte, NC Duration: 6 Months Contract Job Summary We are seeking an experienced AI / Machine Learning Engineer to design ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

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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 Jul 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 engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-demand industries or companies can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially in tech giants or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

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 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.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as AI advances, as they develop and refine algorithms, models, and systems. Roles that require complex problem-solving, creativity, and domain expertise—such as healthcare professionals, data scientists, software developers, cybersecurity specialists, and AI ethics officers—are also expected to persist due to their reliance on human judgment and specialized knowledge. These jobs often involve skills that are difficult for AI to fully replicate or replace.

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 engineers make $300,000 a year?

Senior machine learning engineers and data scientists with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $300,000 or more annually, especially in high-cost-of-living areas or top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on business outcomes.

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 job categories do people searching Machine Learning Engineer jobs in Philadelphia, PA look for? The top searched job categories for Machine Learning Engineer jobs in Philadelphia, PA 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 July 2026, with employment types broken down into 84% Full Time, 14% Part Time, and 2% Contract. Highlights an 85% Physical, 6% Hybrid, and 9% Remote job distribution, with an average salary of $129,939 per year, or $62.5 per hour.
Machine Learning Engineer[C2C/W2 ROLE]

Machine Learning Engineer[C2C/W2 ROLE]

SmartIPlace

Philadelphia, PA • On-site

Contractor

Re-posted 13 days ago


Job description

Job Title: Machine Learning Engineer [w2 role]

Location: Philadelphia, PA (Onsite – 4 days/week at 1800 Arch Street)
Alternate location: Reston, VA (for strong candidates)
Duration: Contract
Eligibility: USC, GC


Job Summary

We are seeking a hands-on Machine Learning Engineer with 5+ years of experience who can design, build, and deploy scalable machine learning solutions. This role requires strong coding expertise and real-world experience delivering models into production environments. The ideal candidate is not a manager but an individual contributor who thrives in a fast-paced, engineering-focused environment.


Key Responsibilities

  • Model Development: Design, build, train, and fine-tune machine learning and deep learning models for real-world use cases
  • Production Deployment: Deploy, monitor, and maintain ML models in production environments
  • Data Pipeline Development: Build and optimize scalable data pipelines for ingestion, transformation, and processing
  • Performance Optimization: Evaluate models using metrics like accuracy, recall, and AUC; optimize for performance and scalability
  • Collaboration: Work closely with cross-functional teams including data engineers, software engineers, and business stakeholders

Required Skills & Qualifications

  • 5+ years of experience as a Machine Learning Engineer or similar role
  • Strong Python programming skills with solid software engineering fundamentals
  • Recent and hands-on experience with PySpark (mandatory)
  • Experience with machine learning frameworks such as Scikit-learn
  • Strong understanding of statistics, probability, and algorithms
  • Experience working with SQL, data modeling, and large datasets
  • Proven track record of deploying ML models into production environments
  • Experience with AWS services

Preferred Qualifications

  • Experience with MLOps tools such as Docker for model deployment
  • Hands-on experience with local Large Language Models (LLMs)
  • Familiarity with distributed computing and big data technologies

Interview Process

Round 1 (30 mins – Virtual)

  • Experience overview
  • Technical discussion
  • Live coding exercise (Video ON + full desktop screen sharing required)

Round 2 (60 mins – In-Person Preferred)

  • Technical deep dive
  • Advanced live coding exercise

Work Environment

  • 4 days onsite preferred (Philadelphia office)
  • Open to relocation candidates
  • Reston, VA location may be considered if needed

Smart-iPlace logo

About Smart-iPlace

Sourced by ZipRecruiter

SMART-iPLACE provides innovative staffing and consulting solutions that help our clients achieve their business objectives. We can understand and support all areas of your IT systems from back-end infrastructure to front-end personal productivity. Our goal is create innovative IT solutions that enable your business to be more agile and competitive.

Industry

It services

Company size

51 - 200 Employees

Headquarters location

Irving, TX, US

Year founded

2021

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