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Freelance Machine Learning Consultant Jobs (NOW HIRING)

Ontrac Solutions

Machine Learning Engineer

Chicago, IL · On-site

$70 - $90/hr

Ontrac Solutions is seeking Machine Learning Engineers to support an urgent staff augmentation ... Experience working in staff augmentation, consulting, or fast-moving client-facing environments.

Alignerr

Machine Learning Engineer

Manhattan, NY · Remote

$154K/yr

Machine Learning Engineer (AI Data Trainer) About the Role What if your machine learning expertise ... Freelance autonomy with the substance of meaningful, high-impact technical work * Gain rare, hands ...

Demoind

Machine Learning

California, PA

PYTHON, ANALYSIS RoleMachine Learning Engineer Industry TypeIT Services & Consulting Functional AreaData Science & Analytics Employment TypeFull Time, Permanent Role CategoryData Science & Machine ...

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

As of Jun 8, 2026, the average hourly pay for freelance machine learning consultant in the United States is $47.71, according to ZipRecruiter salary data. Most workers in this role earn between $24.28 and $61.78 per hour, depending on experience, location, and employer.

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

AspectFreelance Machine Learning ConsultantData Scientist
CredentialsTypically requires degrees in CS, data science, or related fields; certifications in ML or AI are commonUsually holds degrees in statistics, computer science, or related fields; certifications like Certified Data Scientist are beneficial
Work EnvironmentIndependent, project-based, often remote; works with multiple clientsUsually employed by organizations; may work in teams within a company or as a consultant
Industry UsageFreelance roles across various industries including tech, finance, healthcarePrimarily within organizations in sectors like tech, finance, healthcare, research

While both roles involve working with data and machine learning, a Freelance Machine Learning Consultant operates independently on diverse projects, whereas a Data Scientist is typically employed within a company focusing on data analysis and model development. The choice depends on your preference for independent work versus organizational roles.

More about Freelance Machine Learning Consultant jobs
What cities are hiring for Freelance Machine Learning Consultant jobs? Cities with the most Freelance Machine Learning Consultant job openings:
What are the most commonly searched types of Machine Learning Consultant jobs? The most popular types of Machine Learning Consultant jobs are:
What states have the most Freelance Machine Learning Consultant jobs? States with the most job openings for Freelance Machine Learning Consultant jobs include:
What job categories do people searching Freelance Machine Learning Consultant jobs look for? The top searched job categories for Freelance Machine Learning Consultant jobs are:
Freelance Machine Learning Consultant jobs near you
Infographic showing various Freelance Machine Learning Consultant job openings in the United States as of May 2026, with employment types broken down into 40% Full Time, and 60% Part Time. Highlights an 72% Physical, 2% Hybrid, and 26% Remote job distribution, with an average salary of $99,230 per year, or $47.7 per hour.

Machine Learning Engineer

Ontrac Solutions

Chicago, IL • On-site

$70 - $90/hr

Full-time

Posted 9 days ago

Job description

Ontrac Solutions is seeking Machine Learning Engineers to support an urgent staff augmentation engagement for one of our clients.

This role is ideal for junior-to-mid-level engineers with strong Google Cloud Platform experience and a focus on building, maintaining, and supporting production-grade machine learning systems.

The selected engineers will work under the direct guidance of a Staff ML Architect and will focus heavily on daily MLOps execution, pipeline maintenance, model reliability, and production support for a high-traffic digital platform.

Required Credentials
  • 2+ years of experience in machine learning engineering, data engineering, software engineering, or a related technical role.
  • Hands-on experience supporting production or near-production ML systems.
  • Bachelor's degree in Computer Science, Engineering, Data Science, Machine Learning, or equivalent practical experience.
Required Qualifications
  • Solid hands-on experience with the GCP ecosystem, particularly Vertex AI components such as Workbench, Pipelines, and Model Registry.
  • Proficiency with modern ML frameworks, including PyTorch or similar technologies.
  • Experience with containerization tools, especially Docker, for automated builds and deployments.
  • Practical experience managing data processing workflows using Apache Spark and Airflow.
  • Understanding of MLOps best practices, including model deployment, monitoring, training workflows, inference support, and pipeline reliability.
  • Familiarity with real-time model serving and infrastructure tools such as Triton Inference Server and Terraform is highly preferred.
  • Strong problem-solving skills with the ability to troubleshoot, maintain, and optimize ML pipelines in a production environment.
  • Collaborative mindset with the ability to execute technical tasks reliably under the guidance of a senior architect.
Key Responsibilities
  • Support the design, deployment, monitoring, and maintenance of machine learning models in a high-traffic production environment.
  • Maintain, troubleshoot, and optimize end-to-end ML pipelines from raw data ingestion through offline and online model evaluation.
  • Execute daily MLOps tasks, including model training, inference support, pipeline monitoring, and deployment maintenance.
  • Work with tools such as GCP, Vertex AI, Spark, Airflow, Docker, PyTorch, and related MLOps technologies.
  • Build and manage automated containerized deployments to support continuous model operations.
  • Partner closely with the Staff ML Architect and other ML Engineers to ensure models are reliable, scalable, and production-ready.
  • Help identify and resolve performance, reliability, and scalability issues across ML workflows and infrastructure.
Preferred Qualifications
  • Prior experience supporting high-traffic digital platforms or consumer-facing products.
  • Experience with Triton Inference Server, Terraform, or similar infrastructure and real-time serving tools.
  • Experience working in staff augmentation, consulting, or fast-moving client-facing environments.
  • Strong interest in building reliable, production-grade ML systems rather than only experimental or research-focused models.
About Ontrac Solutions

Ontrac Solutions is a strategic consulting and technology solutions firm helping companies Innovate. Create. Elevate. through digital product consulting, cloud solutions, AI-based data solutions, and staff augmentation.

We partner with clients to bring the right technical expertise, execution support, and strategic guidance to complex business and technology initiatives.