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Freelance Google Machine Learning Engineer Jobs in California

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 ...

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 ...

Machine Learning Engineer / Research Engineer Pay: $$110,000 - $165,000 Base Salary + Equity Shift: N/A Location: San Mateo, CA (Peninsula) - Onsite Preferred Schedule: Full time, Permanent Role Visa ...

New

Lead Machine Learning Engineer

San Francisco, CA · On-site +1

$120K - $159K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google ...

Lead Machine Learning Engineer

San Jose, CA · On-site

$120K - $158K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google ...

Lead Machine Learning Engineer

San Jose, CA · On-site +1

$120K - $158K/yr

Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part of ... Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google ...

Machine Learning Engineer Location: Fremont, CA (Local) Onsite interview Duration: 12+ Mos H1B Only h1 candidate About the Role: Our direct client is hiring a Machine Learning Engineer for their ...

Machine Learning Engineer Location: Fremont, CA once the documents are verified, a Codility assessment will be shared with the candidate, where they need to score a minimum of 70% and post that, a ...

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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?

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 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:

Machine Learning Engineer

Framework Ventures

San Francisco, CA • On-site

$120 - $160/hr

Other

Posted 2 days ago

New


Job description

Andalusia Labs is building foundational economic infrastructure for programmable global markets, connecting capital, computation, and coordination across the internet. Our work sits at the intersection of distributed systems, finance, and machine intelligence, with the goal of growing the world’s programmable GDP.

Our team has shipped massively scalable systems and products at Coinbase, Google, AWS, Microsoft, X, TikTok, Goldman Sachs, and High-Frequency Trading firms. We are backed by Coinbase, Mubadala, Lightspeed, Bain Capital, Pantera, Framework, Digital Currency Group, Proof Group, Nima Capital, Naval Ravikant, Arthur Hayes, and founders, GPs, and executives from organizations like Founders Fund, Google, and Coinbase.

Role

We are looking for a talented and driven Machine Learning Engineer who is passionate about building innovative products from 0 to Production. As a Machine Learning Engineer, you will work on a variety of projects related to applied machine learning. You will work closely with the founders, engineers, and other cross‑functional partners and bring new products and business lines to market. This is an amazing opportunity offering you the ability to learn new technical skills in blockchain and work with an amazing team of engineers.

Responsibilities
  • Work closely with the founders, engineers, and other cross‑functional partners to rapidly iterate, experiment, and launch products
  • Improve and optimize LLMs for use in production systems
  • Design and implement scalable data and machine learning pipelines
  • Build best‑in‑class AI chatbots that guide users through their Karak journey by translating research papers, blogs, and technical documentation into more accessible content
  • Participate in discussions from the initial product ideas to launch
  • Understand, build, and help optimize financial algorithms
Requirements
  • BA/BS in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field, or equivalent practical experience
  • 5+ years of systems programming experience working with at least one of these languages (Python, Scala, Java)
  • Experience building machine learning models with ML frameworks such as Tensorflow, PyTorch, and other open‑source frameworks
  • Experience manipulating and optimizing large amounts of structured and unstructured data through pipeline development tools
  • Familiarity with modern software development practices, including version control (Git), continuous integration, and automated testing as applied to Rust, Go, and/or Solidity stacks
  • Highly autonomous, ability to design and develop software with minimal guidance
  • Ability to work in a fast‑paced environment and across the product engineering stack
  • Clear written and verbal communication
Bonus
  • Experience building or working on open‑source ML projects
  • Experience building on EVM, Solana, or Cosmos
  • Experience in algorithmic trading or understanding of traditional finance primitives
  • Founded a company
  • Experience working with startups
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