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Freelance Google Machine Learning Engineer Jobs in Georgia

Senior Machine Learning Engineer

Atlanta, GA

$117K - $155K/yr

The Senior Full-Stack Machine Learning Engineer sits within the Insights Business Unit, which serves as Inovalon's central AI and machine learning hub. This team partners with Provider, Payer, and ...

Senior Machine Learning Engineer

Atlanta, GA

$100K - $138K/yr

Senior Machine Learning Engineer Team: Data & Audience Platform (DAP) - ML Engineering What We Do ... Mosaic, FreeWheel, Google Ad Manager. Agentic AI: Cursor, GitHub Copilot, Amazon Q, Databricks ...

New

Senior Machine Learning Engineer

Atlanta, GA · On-site

$118K - $155K/yr

The Senior Full-Stack Machine Learning Engineer sits within the Insights Business Unit, which serves asInovalon'scentral AI and machine learning hub. This team partners with Provider, Payer, and ...

Senior Machine Learning Engineer

Atlanta, GA · On-site +1

$117K - $155K/yr

The Senior Full-Stack Machine Learning Engineer sits within the Insights Business Unit, which serves as Inovalon's central AI and machine learning hub. This team partners with Provider, Payer, and ...

Staff Machine Learning Engineer

Atlanta, GA · On-site +1

$220K - $280K/yr

As a Staff Machine Learning Engineer, you will lead the technical charge to scale and productionize our core machine learning capabilities. Your work will directly impact key metrics like Time-to-Bet ...

Staff Machine Learning Engineer

Atlanta, GA · On-site +1

$220K - $280K/yr

As a Staff Machine Learning Engineer, you will lead the technical charge to scale and productionize our core machine learning capabilities. Your work will directly impact key metrics like Time-to-Bet ...

Senior Machine Learning Engineer (Nova)

Atlanta, GA · On-site

$100K - $138K/yr

We are looking for a Senior Machine Learning Engineer to build the core Machine Learning foundations that power Nova's agentic experiences. This role focuses on applied Machine Learning in production ...

We are seeking a visionary Machine Learning Engineer Lead to spearhead our experimental ML initiatives and drive innovation across the organization. This role combines technical leadership in cutting ...

We are seeking a visionary Machine Learning Engineer Lead to spearhead our experimental ML initiatives and drive innovation across the organization. This role combines technical leadership in cutting ...

We are seeking a visionary Machine Learning Engineer Lead to spearhead our experimental ML initiatives and drive innovation across the organization. This role combines technical leadership in cutting ...

Machine Learning Lead Engineer

Smyrna, GA · On-site

$134K - $224K/yr

We are seeking a visionary Machine Learning Engineer Lead to spearhead our experimental ML initiatives and drive innovation across the organization. This role combines technical leadership in cutting ...

We are seeking a visionary Machine Learning Engineer Lead to spearhead our experimental ML initiatives and drive innovation across the organization. This role combines technical leadership in cutting ...

We are seeking a visionary Machine Learning Engineer Lead to spearhead our experimental ML initiatives and drive innovation across the organization. This role combines technical leadership in cutting ...

We are seeking a visionary Machine Learning Engineer Lead to spearhead our experimental ML initiatives and drive innovation across the organization. This role combines technical leadership in cutting ...

We are seeking a visionary Machine Learning Engineer Lead to spearhead our experimental ML initiatives and drive innovation across the organization. This role combines technical leadership in cutting ...

We are seeking a visionary Machine Learning Engineer Lead to spearhead our experimental ML initiatives and drive innovation across the organization. This role combines technical leadership in cutting ...

We are seeking a visionary Machine Learning Engineer Lead to spearhead our experimental ML initiatives and drive innovation across the organization. This role combines technical leadership in cutting ...

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Freelance Google Machine Learning Engineer information

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

To thrive as a Freelance Google Machine Learning Engineer, you need a solid background in computer science, statistics, and machine learning, typically supported by a relevant degree and experience with real-world data projects. Familiarity with Google Cloud Platform (GCP), TensorFlow, and certifications like Google Professional Machine Learning Engineer are commonly required. Strong problem-solving abilities, self-motivation, and effective client communication distinguish top freelancers in this field. These skills and qualifications are crucial for delivering robust machine learning solutions tailored to client needs and efficiently navigating remote, project-based work.

What does a Freelance Google Machine Learning Engineer do?

A Freelance Google Machine Learning Engineer is a technical specialist who designs, develops, and deploys machine learning models using Google’s tools and platforms, such as TensorFlow and Google Cloud AI services. They work independently or with clients to solve data-driven problems, build predictive models, and automate processes using machine learning techniques. Their responsibilities may include data preprocessing, feature engineering, model training and evaluation, and integrating models into production systems. Freelancers often manage multiple projects and must stay updated on the latest ML advancements and Google technologies.

What are some common challenges freelance Google Machine Learning Engineers face when working with clients remotely?

Freelance Google Machine Learning Engineers often encounter challenges such as clearly defining project scopes, aligning on deliverables, and managing expectations, especially when working remotely. Communication can be more complex due to time zone differences and varying levels of technical understanding among clients. Staying updated with Google’s latest ML tools and ensuring secure, efficient data sharing are also important. Building strong documentation and regular progress updates can help foster trust and smooth collaboration.

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

AspectFreelance Google Machine Learning EngineerFreelance Data Scientist
CredentialsKnowledge of Google Cloud ML tools, programming skills in Python, TensorFlowStatistical expertise, programming in Python/R, data analysis skills
Work EnvironmentCloud platforms, AI/ML projects, collaboration with developersData analysis, reporting, model development, client communication
Industry UsageTech companies, AI startups, cloud service providersFinance, healthcare, marketing, research organizations

While both roles involve working with data and models, a Freelance Google Machine Learning Engineer specializes in deploying ML solutions on Google Cloud, focusing on AI/ML engineering tasks. A Freelance Data Scientist primarily analyzes data, builds statistical models, and provides insights. The roles overlap in skills but differ in focus and tools used.

What are the most commonly searched types of Google Machine Learning Engineer jobs in Georgia? The most popular types of Google Machine Learning Engineer jobs in Georgia are:
What job categories do people searching Freelance Google Machine Learning Engineer jobs in Georgia look for? The top searched job categories for Freelance Google Machine Learning Engineer jobs in Georgia are:
What cities in Georgia are hiring for Freelance Google Machine Learning Engineer jobs? Cities in Georgia with the most Freelance Google Machine Learning Engineer job openings:
Senior Machine Learning Engineer

Senior Machine Learning Engineer

Inovalon

Atlanta, GA

$117K - $155K/yr

Other

Re-posted 5 days ago


Job description

Inovalon is a leading cloud-based healthcare technology company that leverages data analytics and AI to drive meaningful improvements across the healthcare ecosystem. The Senior Full-Stack Machine Learning Engineer sits within the Insights Business Unit, which serves as Inovalon's central AI and machine learning hub. This team partners with Provider, Payer, and Pharmacy business units to identify, build, and deploy AI solutions that improve clinical and operational outcomes at scale. 

In this role, you will contribute to both classical machine learning and generative AI applications, including LLM-based and agentic solutions. You will work across the full model development lifecycle on a modern, cloud-native AWS stack, collaborating closely with AI Product Managers and a distributed team of senior engineers across the U.S. and India. 

Key Responsibilities
  • Design, train, and deploy machine learning models spanning classical ML (classification, regression, clustering, time-series) and generative AI use cases including LLM-based and agentic applications. 
  • Build and maintain cloud-native solutions on AWS using containerized architectures (Docker, Kubernetes) to support scalable model serving and data pipelines. 
  • Own and contribute to the full Model Development Lifecycle (MDLC), including dataset versioning, model versioning, model registry management, and model evaluation frameworks. 
  • Develop and integrate Python-based ML components that work seamlessly with existing product platforms across multiple business units. 
  • Collaborate with AI Product Managers across the Insights BU and partner business units (Provider, Payer, Pharmacy) to translate business needs into AI solutions. 
  • Apply neural networks and deep learning techniques using PyTorch for appropriate use cases alongside scikit-learn-based classical approaches. 
  • Write robust, production-ready code following engineering best practices; participate in code and design reviews. 
  • Leverage AI coding tools (such as Claude Code or equivalent) as part of your daily development workflow to improve velocity and code quality. 
  • Mentor junior engineers and contribute to team knowledge-sharing around ML best practices, tooling, and architecture decisions. 
  • Support integration of frontend components into ML-powered features where applicable. 
  • Contribute to retrospectives and team process improvements; actively participate in sprint planning and end-of-iteration demos. 
  • Adhere to all HIPAA, data governance, confidentiality, and regulatory requirements in all aspects of work. 
  • Maintain compliance with Inovalon's policies, procedures, and mission statement, fulfilling responsibilities that support operational and financial success. 

Qualifications

Required 

  • Minimum 5 years of software development experience with a strong foundation in machine learning fundamentals and model training. 
  • Expert-level Python proficiency; Python is the team's primary language and is the highest-priority technical requirement. 
  • Hands-on experience building and deploying classical ML models in production using scikit-learn. 
  • Demonstrated experience with generative AI, LLMs, or agentic application development. 
  • Proficiency with PyTorch and neural network architectures. 
  • Practical knowledge of the Model Development Lifecycle (MDLC): dataset versioning, model versioning, model registry, and model evaluation. 
  • AWS cloud experience, including deploying and managing cloud-native workloads. 
  • Containerization experience with Docker and/or Kubernetes. 
  • Strong problem-solving ability; demonstrated capacity to work independently and take ownership of complex technical challenges. 
  • Daily usage of AI-assisted coding tools (e.g., Claude Code, GitHub Copilot, or similar) as part of standard development workflow. 

Preferred 

  • Experience with database technologies (SQL or NoSQL); familiarity with data pipeline tooling. 
  • Frontend development skills to support full-stack ML feature work. 
  • Healthcare domain experience or exposure to HIPAA-regulated environments. 

Education 

  • Bachelor's degree in Computer Science, Data Science, Software Engineering, or a related technical field required. 
  • Master's degree or PhD in Computer Science, Machine Learning, or equivalent practical experience preferred. 

Physical Demands and Work Environment 

  • Sedentary work (i.e., sitting for long periods of time). 
  • Exerting up to 10 pounds of force occasionally and/or a negligible amount of force. 
  • Subject to inside environmental conditions. 
  • Travel for this position will include less than 10% locally, usually for training purposes.