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Machine Learning Engineer Opt Jobs in Philadelphia, PA

Merican

AI / Machine Learning Engineer

PA · On-site

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 ...

Bespoke Labs

Machine Learning Engineer

Trenton, NJ · On-site

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 ...

Bespoke Labs

Machine Learning Engineer

Trenton, NJ

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 ...

Bespoke Labs

Machine Learning Engineer

Wilmington, DE · On-site

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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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 Jul 2, 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:
What cities near Philadelphia, PA are hiring for Machine Learning Engineer Opt jobs? Cities near Philadelphia, PA with the most Machine Learning Engineer Opt job openings:
Machine Learning Engineer Opt jobs near you
Machine Learning Engineer[C2C/W2 ROLE]

Machine Learning Engineer[C2C/W2 ROLE]

SmartIPlace

Philadelphia, PA • On-site

Contractor

Posted 4 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

Social media

Facebook

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