ZipRecruiter

Log In

1

Freelance Machine Learning Engineer Jobs in Philadelphia, PA

BE Group

Senior Machine Learning Engineer

Malvern, PA · 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 ...

Vangard, Inc.

Senior Machine Learning Engineer

Malvern, PA

$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.

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

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 ...

next page

Showing results 1-20

All JobsMachine Learning Engineer JobsFreelance Machine Learning Engineer JobsFreelance Machine Learning Engineer Jobs in Philadelphia, PA

Freelance Machine Learning Engineer information

See Philadelphia, PA salary details

$15

$48

$133

How much do freelance machine learning engineer jobs pay per hour?

As of Aug 1, 2026, the average hourly pay for freelance machine learning engineer in Philadelphia, PA is $48.14, according to ZipRecruiter salary data. Most workers in this role earn between $24.52 and $62.36 per hour, depending on experience, location, and employer.

What does a Freelance Machine Learning Engineer do?

A Freelance Machine Learning Engineer designs, develops, and implements machine learning models and algorithms for clients on a project basis. They work independently to analyze data, build predictive models, and help businesses solve complex problems using AI and machine learning techniques. Their responsibilities may also include data preprocessing, model evaluation, and deploying solutions into production environments. Freelance Machine Learning Engineers often collaborate remotely with teams and must manage their own schedules and client relationships.

What are the key skills and qualifications needed to thrive as a Freelance Machine Learning Engineer, and why are they important?

To thrive as a Freelance Machine Learning Engineer, you need expertise in programming (especially Python), a solid grasp of machine learning algorithms, and a relevant academic background such as a degree in computer science, mathematics, or engineering. Familiarity with frameworks like TensorFlow or PyTorch, cloud platforms (AWS, GCP, Azure), and experience with version control systems are typically required. Strong problem-solving, self-management, and client communication skills help set successful freelancers apart. These competencies are crucial for delivering effective solutions, managing projects independently, and building client trust in a competitive market.

How do freelance machine learning engineers typically manage client expectations and project scopes?

Freelance machine learning engineers often work with clients who may not have a deep technical understanding of AI or data science. A common challenge is clearly defining the project scope and deliverables at the outset, ensuring both parties understand what is feasible given the data, time, and budget constraints. Successful freelancers use regular progress updates, milestone-based deliverables, and transparent communication to manage expectations and avoid scope creep. Building trust through clear documentation and setting realistic timelines also helps foster long-term client relationships.

What is the difference between Freelance Machine Learning Engineer vs Data Scientist?

AspectFreelance Machine Learning EngineerData Scientist
CredentialsTypically requires a degree in computer science, data science, or related fields; certifications in machine learning or AI are a plusUsually holds a degree in statistics, data science, or related areas; certifications in data analysis or visualization are common
Work EnvironmentIndependent, project-based work often remotely for various clientsOften employed full-time in organizations or consulting roles, sometimes freelance
Industry UsageUsed across tech, finance, healthcare, and startups for deploying ML modelsApplied in research, analytics, and strategic decision-making across industries

Freelance Machine Learning Engineers focus on developing and deploying ML models independently for diverse clients, while Data Scientists analyze data to extract insights, often working within organizations. Both roles require strong technical skills, but their work scope and environment differ significantly.

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 Freelance Machine Learning Engineer jobs in Philadelphia, PA? For Freelance Machine Learning Engineer jobs in Philadelphia, PA, the most frequently searched job titles are:
What job categories do people searching Freelance Machine Learning Engineer jobs in Philadelphia, PA look for? The top searched job categories for Freelance Machine Learning Engineer jobs in Philadelphia, PA are:
What cities near Philadelphia, PA are hiring for Freelance Machine Learning Engineer jobs? Cities near Philadelphia, PA with the most Freelance Machine Learning Engineer job openings:
Freelance Machine Learning Engineer jobs near you

Machine Learning Engineer - Databricks

Aptino

Malvern, PA • On-site

Other

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

Job description

Role: Machine Learning Engineer – Databricks

Location: Malvern, PA (Hybrid – 3 days/week onsite)
Duration: 12 Months

Position Overview:

We are seeking an experienced Machine Learning Engineer with strong expertise in the Databricks Lakehouse Platform to develop, deploy, and optimize scalable AI/ML solutions. The ideal candidate will have hands-on experience building production-ready machine learning models, implementing MLOps best practices, and designing end-to-end ML pipelines using Databricks, Spark, and AWS cloud services.

Key Responsibilities:
  • Design, develop, and deploy scalable machine learning models using the Databricks Machine Learning platform.
  • Build and optimize end-to-end ML pipelines, including data ingestion, feature engineering, model training, validation, deployment, and monitoring.
  • Utilize MLflow for experiment tracking, model versioning, lifecycle management, and production deployments.
  • Develop high-performance data processing pipelines using PySpark, Apache Spark, and SQL to support large-scale analytics and machine learning workloads.
  • Build and maintain production-grade applications and ML workflows on AWS, leveraging services such as Lambda, S3, Glue, ECS/EKS, Step Functions, SageMaker, and Bedrock.
  • Implement feature engineering, model evaluation, hyperparameter optimization, and performance tuning to improve model accuracy and scalability.
  • Collaborate with data engineers, data scientists, and business stakeholders to translate business requirements into production-ready ML solutions.
  • Establish MLOps best practices, CI/CD processes, monitoring strategies, and governance standards for machine learning deployments.
  • Optimize data architecture and machine learning workflows using Databricks Lakehouse, Delta Lake, and Unity Catalog.
  • Contribute to AI innovation initiatives by evaluating emerging technologies, Generative AI use cases, and modern machine learning frameworks.
Required Qualifications:
  • 5+ years of experience in Machine Learning, Artificial Intelligence, or Data Science engineering.
  • Strong hands-on expertise with Databricks Machine Learning and the Databricks ecosystem.
  • Proven experience using MLflow for experiment management, model registry, and deployment.
  • Strong programming skills in Python, PySpark, Apache Spark, and SQL.
  • Experience developing supervised and unsupervised machine learning models for enterprise applications.
  • Hands-on experience building, deploying, and supporting production-grade ML pipelines.
  • Solid understanding of feature engineering, model validation, hyperparameter tuning, and model performance optimization.
  • Experience developing cloud-native AI/ML solutions on AWS.
  • Experience building scalable data pipelines using Spark, Glue, Airflow, dbt, or similar orchestration tools.
  • Strong analytical, troubleshooting, and problem-solving skills with experience handling large datasets.
Preferred Qualifications:
  • Experience designing solutions on the Databricks Lakehouse Architecture.
  • Knowledge of Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), or AI-powered applications.
  • Experience with orchestration frameworks such as Apache Airflow or Azure Data Factory.
  • Familiarity with Docker, Kubernetes, CI/CD, and modern DevOps practices.
  • Hands-on experience with Delta Lake, Unity Catalog, and enterprise data governance.
  • Databricks certification is an added advantage.

Apply