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Freelance Google Machine Learning Engineer Jobs in California

Prosum Inc.

Machine Learning Engineer

CA · On-site

$75 - $89/hr

Machine Learning Engineer Pay Rate: $75-$89/hour Position Summary We are seeking a skilled Machine ... Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform * Experience with ...

RAPID EAGLE INC

Machine Learning Engineer

Sunnyvale, CA · Remote

$70 - $80/hr

Health insurance Machine Learning Engineer 100% Remote We are seeking a highly skilled Machine Learning Engineer to design, develop, deploy, and maintain scalable machine learning solutions that ...

Willing Tech

Machine Learning Engineer

San Francisco, CA · On-site +1

$172K - $384K/yr

They're now looking for a Machine Learning Engineer to help build the next generation of AI-powered tools that generate structured visuals from scientific inputs . If you're excited by real-world ...

NTENT

Machine Learning Engineer

Carlsbad, CA · On-site

Machine Learning Engineer Position: Full time Location: Carlsbad office About Us: NTENT provides a Platform-as-a-Service (PaaS), allowing industry partners to customize, localize and integrate search ...

NTENT

Machine Learning Engineer

Carlsbad, CA

Machine Learning Engineer Position: Full time Location: Carlsbad office About Us: NTENT provides a Platform-as-a-Service (PaaS), allowing industry partners to customize, localize and integrate search ...

RIT Solutions

Machine Learning Engineer

Fremont, CA

Machine Learning Engineer Location: Fremont, CA Duration: 12+ Months Tesla/ $65 About the Role Our direct client is seeking a highly skilled Machine Learning Engineer to join their Software Machine ...

Poesis LLC

Machine Learning Engineer

Menlo Park, CA

Poesis Machine Learning Engineer At Poesis, machine learning and artificial intelligence open the door to improved alpha discovery, higher quality decision-making and intelligent risk management. We ...

LeanData

Machine Learning Engineer

Santa Clara, CA

Machine Learning Engineer LeanData helps the world's fastest-growing companies automate, simplify, and accelerate revenue. We are looking for a curious and innovative Machine Learning Engineer to ...

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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 California? The most popular types of Google Machine Learning Engineer jobs in California are:
What are popular job titles related to Freelance Google Machine Learning Engineer jobs in California? For Freelance Google Machine Learning Engineer jobs in California, the most frequently searched job titles are:
What job categories do people searching Freelance Google Machine Learning Engineer jobs in California look for? The top searched job categories for Freelance Google Machine Learning Engineer jobs in California are:
What cities in California are hiring for Freelance Google Machine Learning Engineer jobs? Cities in California with the most Freelance Google Machine Learning Engineer job openings:
Freelance Google Machine Learning Engineer jobs near you
Machine Learning Engineer

Machine Learning Engineer

Prosum Inc.

CA • On-site

$75 - $89/hr

Contractor

Posted 12 days ago

Job description

Job Description
Machine Learning Engineer
Pay Rate: $75-$89/hour
Position Summary
We are seeking a skilled Machine Learning Engineer (MLOps) to support the full lifecycle of machine learning models, including design, development, deployment, and maintenance. This role focuses on building scalable, production-ready AI/ML solutions and ensuring seamless integration within existing systems.
The ideal candidate will collaborate with cross-functional teams to deploy, monitor, and optimize machine learning models that drive operational efficiency, innovation, and data-driven decision-making. This position requires strong experience in MLOps, DevOps practices, and cloud-based AI infrastructure.
Key Responsibilities
  • Design, build, deploy, and maintain machine learning models in production environments
  • Develop and manage end-to-end MLOps pipelines, including model versioning, monitoring, and automation
  • Implement scalable ML infrastructure using cloud platforms (AWS, Azure, or GCP)
  • Build and optimize CI/CD pipelines for automated testing and deployment of ML models
  • Collaborate with data scientists, data engineers, and DevOps teams to operationalize AI solutions
  • Monitor model performance, system health, and data drift; implement logging and alerting solutions
  • Ensure reliability, scalability, and performance of ML systems in real-time inference environments
  • Maintain version control for models and code to support reproducibility and collaboration
  • Apply best practices for testing, debugging, and performance optimization
  • Ensure compliance with data security, privacy, and regulatory standards
  • Create and maintain technical documentation for ML systems and processes
Required Qualifications
  • Bachelor's degree in Computer Science, Engineering, Artificial Intelligence, or a related field
  • 3+ years of experience in machine learning engineering or MLOps
  • Hands-on experience managing the end-to-end machine learning lifecycle
  • Strong programming skills in Python, R, and/or SQL
  • Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform
  • Experience with containerization (Docker) and orchestration tools (Kubernetes)
  • Experience with infrastructure as code tools such as Terraform
  • Experience building and maintaining CI/CD pipelines (e.g., GitHub Actions)
  • Strong understanding of software development, system architecture, and deployment processes
  • Experience with monitoring, logging, and performance tuning of ML systems
  • Knowledge of version control systems (e.g., Git)
Preferred Qualifications
  • Master's degree in Computer Science, Engineering, or a related field
  • Experience working with healthcare data or regulated environments
  • Familiarity with Electronic Health Record (EHR) systems
  • Experience with predictive modeling, natural language processing (NLP), and large language models (LLMs)
  • Knowledge of retrieval-augmented generation (RAG) frameworks and their applications
  • Understanding of agile methodologies and DevOps lifecycle practices
Core Competencies
  • Production-grade ML model deployment and lifecycle management
  • Scalable infrastructure design for AI/ML workloads
  • Cross-functional collaboration and technical leadership
  • Strong analytical and problem-solving skills
  • Effective technical communication and documentation

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