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Remote Machine Learning Architect Jobs in California

Alt

Machine Learning Engineer

San Francisco, CA · On-site +1

$196K/yr

... specifications, architecture diagrams, data-flow documentation, and systems integration ... Fully remote position (100%) from anywhere in U.S. reporting to HQ in San Francisco, CA JOB ...

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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

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 ...

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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 June 2026, with employment types broken down into 78% Full Time, 13% Part Time, 6% Temporary, and 3% Contract. Highlights an 38% Physical, 3% Hybrid, and 59% Remote job distribution.
Machine Learning Engineer

Machine Learning Engineer

Alt

San Francisco, CA • On-site, Remote

$196K/yr

Other

Posted 2 days ago

Job description

REFERRALS: The below position is eligible for employee incentives provided pursuant to Alt Platform Inc.'s referrals policy, which is described in detail at https://app.notion.com/p/altxyz/Hiring-Referral-program-29d859d114314e39886ae51c9fb1bdf9?source=copy_link

EMPLOYER NAME: Alt Platform Inc.

JOB TITLE: Machine Learning Engineer (Full time)

JOB DUTIES: The Machine Learning Engineer will design, develop, deploy, and maintain advanced machine learning models and data analysis systems to support specialized domain modeling and proprietary feature engineering. The person in this role will analyze structured and unstructured datasets, perform applied experimentation, develop production-grade machine learning pipelines, optimize modeling infrastructure, and collaborate across business and engineering teams to translate business needs into scalable data-driven solutions. The Machine Learning Engineer will be primarily responsible for the following duties:

  • Conduct applied research and experimentation to design, train, evaluate, and refine machine learning models, including performing feature engineering, selecting modeling techniques, validating model performance, and documenting analytical methods.
  • Develop, test, and deploy production machine learning systems by managing the complete MLOps lifecycle, including experiment tracking, model versioning, containerization, orchestration of automated workflows, and monitoring of model performance in production environments.
  • Maintain and optimize machine learning infrastructure to support training, inference, and data processing workflows, including configuring cloud compute environments, tuning distributed computation jobs, and improving system efficiency and scalability.
  • Collaborate with business stakeholders to translate analytical requirements into quantifiable modeling objectives, define evaluation criteria, validate assumptions with data, and communicate analytical findings and modeling results.
  • Design, prepare, and review technical documentation, including model design specifications, architecture diagrams, data-flow documentation, and systems integration requirements to support maintainability and long-term scalability.
  • Develop AI-driven automation solutions using Large Language Models to streamline internal workflows, design LLM-based agentic processes, validate automated outputs, and measure accuracy and efficiency improvements.
  • Design and develop internal software tools and backend services that support data quality, enable analytical workflows, expose model insights to internal teams, and integrate with organizational data systems and APIs.

No travel is required.

Fully remote position (100%) from anywhere in U.S. reporting to HQ in  San Francisco, CA 

JOB REQUIREMENTS: Master's degree (or foreign equivalent) in data science, economics, mathematics or computer science and 1 year of experience in any occupations in which required experiences were acquired (may be pre-Master's).  Professional experiences must include:

  • 1 year of experience designing, training, and evaluating machine learning models using Python-based data science libraries, including experience performing feature engineering and developing predictive and descriptive models using tools such as scikit-learn and pandas.
  • Experience using machine-learning lifecycle tools, including MLflow (or similar platforms) for experiment tracking, reproducible training workflows, and model versioning.
  • Experience using Docker for containerization to package machine learning pipelines and ensure reproducible deployment environments.
  • 1 year of experience orchestrating data processing and machine learning workflows, including scheduling, monitoring, and managing dependencies using Apache Airflow.
  • 1 year of experience using CI/CD tools to automate model training, testing, and deployment processes.
  • 1 year of experience configuring and optimizing cloud compute environments to support training, inference, and large-scale data processing tasks.
  • 1 year of experience developing AI-driven automation workflows using language models, including integrating language-based model components into analytical or operational processes.
  • Experience developing backend services and APIs using FastAPI, REST, or GraphQL to support data access, model serving, and analytical tooling.
  • 1 year of experience working with SQL databases, including PostgreSQL, and cloud data platforms (e.g., Snowflake), including writing analytical queries and implementing data-quality validation workflows.
  • Experience using distributed data-processing tools, including Spark, for large-scale data transformation and feature-engineering operations.

SALARY OFFERED: From $196,776 per year

JOB LOCATION: San Francisco, CA

TO APPLY SEND RESUME TO: Eryn@alt.xyz (write "Machine Learning Engineer" in subject line)

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