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Independent Contractor Aws Machine Learning Jobs

Eccalon LLC

Machine Learning Engineer

Detroit, MI

Putting your model into production using AWS or GCP. Required Qualifications * BS. in Computer ... Ability to work independently, and within a team. * Ability to communicate effectively with non ...

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Independent Contractor Aws Machine Learning information

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$394

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$2.1K

How much do independent contractor aws machine learning jobs pay per week?

As of Jun 26, 2026, the average weekly pay for independent contractor aws machine learning in the United States is $1,089.33, according to ZipRecruiter salary data. Most workers in this role earn between $721.15 and $1,211.54 per week, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Independent Contractor AWS Machine Learning Specialist, and why are they important?

To thrive as an Independent Contractor AWS Machine Learning Specialist, you need expertise in machine learning algorithms, data analysis, and proficiency with Python, as well as a strong understanding of AWS services like SageMaker and Lambda. Familiarity with cloud-based ML tools, experience with data pipelines, and AWS certifications such as AWS Certified Machine Learning – Specialty are highly valued. Exceptional problem-solving, communication, and project management skills help you collaborate with clients and deliver solutions efficiently. These skills ensure you can design, implement, and optimize machine learning models in scalable cloud environments, meeting diverse client needs.

What does an Independent Contractor specializing in AWS Machine Learning do?

An Independent Contractor specializing in AWS Machine Learning works on a freelance or contract basis to design, develop, and deploy machine learning solutions using Amazon Web Services. They may help clients with data preparation, model training, and integration of machine learning models into existing systems using AWS tools like SageMaker, Lambda, and S3. Their responsibilities often include consulting on best practices, optimizing workflows, and ensuring scalable, secure machine learning infrastructures in the cloud.

What is the difference between Independent Contractor Aws Machine Learning vs Data Scientist?

AspectIndependent Contractor Aws Machine LearningData Scientist
CredentialsCertifications in AWS, Machine Learning, and cloud computingDegree in Data Science, Statistics, or related field; often certifications like SAS or Python
Work EnvironmentFreelance, project-based, remote or on-site in cloud environmentsFull-time, corporate or research settings, often in office or remote
Employer & IndustryClients across various industries using AWS cloud servicesOrganizations in tech, finance, healthcare, and research sectors

While both roles involve data analysis and machine learning, an Independent Contractor Aws Machine Learning specializes in deploying models on AWS cloud platforms as a freelancer, whereas a Data Scientist typically works within organizations analyzing data and building models in a more permanent role.

What are some common challenges faced by independent contractors working on AWS Machine Learning projects, and how can they be managed?

Independent contractors in AWS Machine Learning often face challenges such as staying updated with rapidly evolving AWS services, managing project scope with limited resources, and ensuring data security and compliance. To address these, it's important to regularly participate in AWS training, maintain clear communication with clients about project expectations, and follow best practices for security and data handling. Proactively setting up efficient workflows and leveraging AWS documentation and community forums can also help manage technical and logistical hurdles.
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Independent Contractor Aws Machine Learning jobs near you
Infographic showing various Independent Contractor Aws Machine Learning job openings in the United States as of June 2026, with employment types broken down into 78% Full Time, 14% Part Time, and 8% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $56,645 per year, or $27.2 per hour.

Machine Learning Engineer

Pivotal Solutions

Manhattan, NY • On-site

Full-time

Medical, Dental, Vision

Posted 11 days ago

Job description


Job Overview:
We are seeking a skilled Machine Learning Engineer to join our team. The ideal candidate will be responsible for designing, developing, and deploying machine learning models to solve real-world problems. You will work closely with data scientists, software engineers, and business stakeholders to implement advanced machine learning solutions and drive innovation within the company.
Key Responsibilities:
  • Design and develop scalable machine learning models and algorithms.
  • Collaborate with cross-functional teams to integrate machine learning models into production systems.
  • Analyze large datasets to extract actionable insights and identify patterns.
  • Tune and optimize machine learning models for performance and accuracy.
  • Stay current with the latest advancements in AI and machine learning technologies.
  • Work with software development teams to ensure models are deployed efficiently and effectively.
  • Develop and maintain documentation for models, algorithms, and tools used.

Requirements
  • Bachelor's or Master's degree in Computer Science, Mathematics, or related field.
  • Proven experience in machine learning, data science, and AI technologies.
  • Proficiency in Python, R, or other programming languages used in machine learning.
  • Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
  • Strong understanding of data structures, algorithms, and statistical modeling.
  • Familiarity with cloud platforms (AWS, GCP, Azure) for deploying machine learning models.
  • Excellent problem-solving skills and the ability to work independently or in a team.
  • Strong communication skills to explain technical concepts to non-technical stakeholders.

Preferred:
  • Experience with deep learning techniques and natural language processing (NLP).
  • Prior experience in deploying machine learning models in a production environment.
  • Familiarity with DevOps practices and tools for machine learning pipelines (e.g., Docker, Kubernetes).

Benefits:
  • Competitive salary and performance bonuses.
  • Health, dental, and vision insurance.
  • Flexible working hours and remote work options.
  • Professional development opportunities.

Apply