ZipRecruiter

Log In

2

Remote Machine Learning Architect Jobs in California

DocuSign

Machine Learning Engineer

San Francisco, CA · On-site +1

$164K - $266K/yr

Architect sophisticated Retrieval-Augmented Generation (RAG) pipelines and advanced context ... Employee divides their time between in-office and remote work. Access to an office location is ...

Capital One

Lead Machine Learning Engineer

San Jose, CA · On-site +1

$120K - $158K/yr

You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have ...

Capital One

Lead Machine Learning Engineer

San Francisco, CA · On-site +1

$120K - $159K/yr

You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have ...

Capital One

Sr. Lead Machine Learning Engineer

San Jose, CA · On-site +1

$120K - $158K/yr

You'll focus on machine learning architectural design, develop and review model and application code, and ensure high availability and performance of our machine learning applications. You'll have ...

next page

Showing results 1-20

All JobsMachine Learning Architect JobsRemote Machine Learning Architect JobsRemote Machine Learning Architect Jobs in California

Remote Machine Learning Architect information

How does a Remote Machine Learning Architect typically collaborate with distributed teams to deliver successful projects?

As a Remote Machine Learning Architect, effective collaboration with globally distributed teams is essential. You will often coordinate with data scientists, software engineers, and business stakeholders via virtual meetings, shared documentation, and project management tools. Regular communication, clear documentation of model designs, and version control practices are crucial to ensure alignment and smooth integration of machine learning solutions. Adopting agile methodologies and being proactive in addressing time zone differences help maintain project momentum and foster a productive team environment.

What is the difference between Remote Machine Learning Architect vs Data Scientist?

AspectRemote Machine Learning ArchitectData Scientist
Required CredentialsMaster's or PhD in CS, AI, or related fields; certifications in ML frameworksMaster's in Data Science, Statistics, or related; certifications in data analysis tools
Work EnvironmentDesigning ML systems, collaborating with engineering teams, remote or on-siteAnalyzing data, building models, often remote or in-office
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, tech

Remote Machine Learning Architects focus on designing and implementing scalable ML systems, while Data Scientists analyze data and build models. Both roles require advanced degrees and often overlap in skills, but their core responsibilities differ in scope and focus.

What is a Remote Machine Learning Architect?

A Remote Machine Learning Architect is a professional who designs, builds, and oversees machine learning systems and infrastructure while working remotely. They collaborate with data scientists, engineers, and stakeholders to define system architecture, select appropriate algorithms, and ensure scalable deployment of machine learning models. Their responsibilities include setting technical standards, optimizing workflows, and ensuring integration with existing IT infrastructure, all accomplished through remote communication and collaboration tools. This role requires strong expertise in machine learning, cloud platforms, and software engineering.

What are the key skills and qualifications needed to thrive as a Remote Machine Learning Architect, and why are they important?

To thrive as a Remote Machine Learning Architect, you need deep expertise in machine learning algorithms, model development, and a solid background in computer science or related fields, often supported by an advanced degree. Familiarity with cloud platforms (such as AWS, Azure, or GCP), deep learning frameworks (like TensorFlow or PyTorch), and relevant certifications are typically expected. Strong problem-solving, communication, and project management skills help you collaborate effectively with distributed teams and stakeholders. These skills and qualities are crucial for designing scalable ML solutions that drive business value in a remote work environment.
What are popular job titles related to Remote Machine Learning Architect jobs in California? For Remote Machine Learning Architect jobs in California, the most frequently searched job titles are:
What job categories do people searching Remote Machine Learning Architect jobs in California look for? The top searched job categories for Remote Machine Learning Architect jobs in California are:
What cities in California are hiring for Remote Machine Learning Architect jobs? Cities in California with the most Remote Machine Learning Architect job openings:
Remote Machine Learning Architect jobs near you
Infographic showing various Remote Machine Learning Architect job openings in California as of July 2026, with employment types broken down into 92% Full Time, 4% Part Time, and 4% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.

Machine Learning Technical Lead, Artificial Intelligence (AI) Required, Work From Home

Ginas Tech Jobs

San Francisco, CA • Remote

Full-time

Medical, Dental, Vision, PTO

Posted 15 days ago

Job description

Job Description

Machine Learning Technical Lead, Artificial Intelligence (AI) Required, Work From Home

As Machine Learning Technical Lead, you own the execution layer of intelligence.  You will translate research direction into reliable, scalable, production-grade ML systems.  This role sits at the intersection of research, infrastructure, and product.  You will be responsible for making models trainable, deployable, observable, and performant under real-world constraints.  This position is 100% Remote.

Machine Learning Technical Lead Responsibilities:

- Own end-to-end ML system execution:  data pipelines, training workflows, evaluation systems, inference architecture, and deployment.

- Fine-tune and adapt models using state-of-the-art methods such as LoRA, QLoRA, SFT, DPO, and distillation.

- Architect and operate scalable inference systems, balancing latency, cost, and reliability.

- Design and maintain data systems for high-quality synthetic and real-world training data.

- Implement evaluation pipelines covering performance, robustness, safety, and bias, in partnership with research leadership.

- Own production deployment, including GPU optimization, memory efficiency, latency reduction, and scaling policies.

- Collaborate closely with application engineering to integrate ML systems cleanly into backend, mobile, and desktop products.

- Make pragmatic trade-offs and ship improvements quickly, learning from real usage.

- Work under real production constraints: latency, cost, reliability, and safety

Machine Learning Technical Lead Outcomes:

- Research and models reliably translate into production-ready solutions with clear performance and quality targets.

- ML pipelines, training loops, and inference systems are stable, efficient, and maintainable.

- Production issues are detected, debugged, and resolved quickly, minimizing user impact.

- Team members are supported, aligned, and able to deliver high-impact ML work with minimal friction.

- Iterations on models and systems are measurable, safe, and improve user experience over time.

Qualifications

Machine Learning Technical Lead Qualifications:

- Experience building or shipping real Machine Learning systems used by people, not just demos.

- Artificial Intelligence (AI) experience required.

- Experience working with large models and understanding their failure modes.

- Experience writing strong, production-grade code.

- You are self-directed, pragmatic, and take full ownership of outcomes.

- You communicate clearly and collaborate well in small, high-trust teams.

- Tech Stack:  GPU-based training and inference system, JAX, Python, and PyTorch.

Benefits include medical insurance, Dental, Vision, Savings Plan Options, PTO, etc.

Keywords:  San Francisco CA Jobs, Machine Learning Technical Lead, AI, Artificial Intelligence, Distillation, DPO, GPU Optimization, JAX, LoRA, Machine Learning, Python, PyTorch, QLoRA, SFT, Technical Lead, Work From Home, Remote, California Recruiters, IT Jobs, California Recruiting

Looking to hire a Machine Learning Technical Lead in San Francisco, CA or in other cities?  Our IT recruiting agencies and staffing companies can help.

We help companies that are looking to hire Machine Learning Technical Leads for jobs in San Francisco, California and in other cities too.  Please contact our IT recruiting agencies and IT staffing companies today!

Additional Information

Please check out all of our jobs at www.ginastechjobs.com.

Apply