Job Summary : Scale AI is the data foundation for AI, helping organizations build and deploy ... agent patterns) into maintainable, observable systems. • Own deployment, monitoring, and ...
Job Summary : Scale AI is the data foundation for AI, helping organizations build and deploy ... agent patterns) into maintainable, observable systems. • Own deployment, monitoring, and ...
Applied AI Engineer
San Francisco, CA · On-site +1
$150K - $300K/yr
Experiment with the latest LLM orchestration patterns and context management techniques for ... learning, AI research, or applied AI engineering * Strong background in LLMs, RAG systems, and ...
Applied AI Engineer
San Francisco, CA · On-site +1
$150K - $300K/yr
Experiment with the latest LLM orchestration patterns and context management techniques for ... learning, AI research, or applied AI engineering * Strong background in LLMs, RAG systems, and ...
... batch patterns). * Demonstrated success enabling self-service BI and analytics platforms with governed semantic layers. * Exposure to machine learning/AI platforms and MLOps practices for ...
... batch patterns). * Demonstrated success enabling self-service BI and analytics platforms with governed semantic layers. * Exposure to machine learning/AI platforms and MLOps practices for ...
... batch patterns). * Demonstrated success enabling self-service BI and analytics platforms with governed semantic layers. * Exposure to machine learning/AI platforms and MLOps practices for ...
... batch patterns). * Demonstrated success enabling self-service BI and analytics platforms with governed semantic layers. * Exposure to machine learning/AI platforms and MLOps practices for ...
... batch patterns). * Demonstrated success enabling self-service BI and analytics platforms with governed semantic layers. * Exposure to machine learning/AI platforms and MLOps practices for ...
Quick apply
... batch patterns). * Demonstrated success enabling self-service BI and analytics platforms with governed semantic layers. * Exposure to machine learning/AI platforms and MLOps practices for ...
... batch patterns). * Demonstrated success enabling self-service BI and analytics platforms with governed semantic layers. * Exposure to machine learning/AI platforms and MLOps practices for ...
... batch patterns). * Demonstrated success enabling self-service BI and analytics platforms with governed semantic layers. * Exposure to machine learning/AI platforms and MLOps practices for ...
... batch patterns). * Demonstrated success enabling self-service BI and analytics platforms with governed semantic layers. * Exposure to machine learning/AI platforms and MLOps practices for ...
... batch patterns). * Demonstrated success enabling self-service BI and analytics platforms with governed semantic layers. * Exposure to machine learning/AI platforms and MLOps practices for ...
Senior Software Engineer
San Francisco, CA · On-site
$175K - $200K/yr
Set and uphold coding standards, architectural patterns, and review processes; mentor engineers. Co ... Passion for engineering and learning. * AI fluency, and ability to build with AI at the core
Senior Software Engineer
San Francisco, CA · On-site
$175K - $200K/yr
Set and uphold coding standards, architectural patterns, and review processes; mentor engineers. Co ... Passion for engineering and learning. * AI fluency, and ability to build with AI at the core
Intern
San Francisco, CA · On-site
$17.75 - $23.50/hr
Discover patterns, trends, and predictive signals in large datasets using statistical modeling, machine learning, and AI techniques. * Apply data segmentation, forecasting, and optimization methods ...
Intern
San Francisco, CA · On-site
$17.75 - $23.50/hr
Discover patterns, trends, and predictive signals in large datasets using statistical modeling, machine learning, and AI techniques. * Apply data segmentation, forecasting, and optimization methods ...
We apply art of Artificial Intelligence/Machine Learning (AI/ML) to the conversational problems and ... patterns, and driving improvements through system changes or training data enhancements.
We apply art of Artificial Intelligence/Machine Learning (AI/ML) to the conversational problems and ... patterns, and driving improvements through system changes or training data enhancements.
Senior Application Security Engineer, AI and Machine Learning
San Francisco, CA · On-site +1
$134K - $185K/yr
Build secure patterns for authentication, authorization, and service to service communication ... AI and machine learning. Compensation
Senior Application Security Engineer, AI and Machine Learning
San Francisco, CA · On-site +1
$134K - $185K/yr
Build secure patterns for authentication, authorization, and service to service communication ... AI and machine learning. Compensation
Machine Learning Engineer
Palo Alto, CA · On-site
AI's strategic objectives. Key Responsibilities: * Design, build, and maintain end-to-end ML ... Solid foundation in computer science fundamentals (data structures, algorithms, design patterns ...
Machine Learning Engineer
Palo Alto, CA · On-site
AI's strategic objectives. Key Responsibilities: * Design, build, and maintain end-to-end ML ... Solid foundation in computer science fundamentals (data structures, algorithms, design patterns ...
AI's strategic objectives. Key Responsibilities: * Design, build, and maintain end-to-end ML ... Solid foundation in computer science fundamentals (data structures, algorithms, design patterns ...
AI's strategic objectives. Key Responsibilities: * Design, build, and maintain end-to-end ML ... Solid foundation in computer science fundamentals (data structures, algorithms, design patterns ...
Senior Machine Learning Engineer - GenAI, LLM, Agentic AI
Santa Clara, CA · On-site
$153K - $225K/yr
Understanding of distributed system design patterns and microservices architecture. * Demonstrable ... learning work experience. Preferred Qualifications: * Research experience in agentic AI or related ...
Senior Machine Learning Engineer - GenAI, LLM, Agentic AI
Santa Clara, CA · On-site
$153K - $225K/yr
Understanding of distributed system design patterns and microservices architecture. * Demonstrable ... learning work experience. Preferred Qualifications: * Research experience in agentic AI or related ...
ServiceNow Solution Architect - US
San Jose, CA · On-site
$73.75 - $97.25/hr
... patterns. Learning Platform Enablement • Partner with engineering teams to translate business requirements into technical designs. • Define technical architecture for AI-powered Learning ...
ServiceNow Solution Architect - US
San Jose, CA · On-site
$73.75 - $97.25/hr
... patterns. Learning Platform Enablement • Partner with engineering teams to translate business requirements into technical designs. • Define technical architecture for AI-powered Learning ...
ServiceNow Solution Architect - US
San Jose, CA · On-site
$73.75 - $97.25/hr
... patterns. Learning Platform Enablement Partner with engineering teams to translate business requirements into technical designs. Define technical architecture for AI-powered Learning including in ...
ServiceNow Solution Architect - US
San Jose, CA · On-site
$73.75 - $97.25/hr
... patterns. Learning Platform Enablement Partner with engineering teams to translate business requirements into technical designs. Define technical architecture for AI-powered Learning including in ...
Senior Application Security Engineer, AI and Machine Learning
San Francisco, CA · On-site
$134K - $185K/yr
Build secure patterns for authentication, authorization, and service to service communication ... AI and Machine Learning Experience * Experience securing ML pipelines, inference systems, or data ...
Senior Application Security Engineer, AI and Machine Learning
San Francisco, CA · On-site
$134K - $185K/yr
Build secure patterns for authentication, authorization, and service to service communication ... AI and Machine Learning Experience * Experience securing ML pipelines, inference systems, or data ...
Associate Consultant - Data and AI Practice
San Francisco, CA · On-site +1
$100K - $180K/yr
Working closely with clients, you will assist in prototyping and piloting AI and machine learning ... patterns, and platform scalability, enabling trusted, value-driven, and compliant data and AI ...
Associate Consultant - Data and AI Practice
San Francisco, CA · On-site +1
$100K - $180K/yr
Working closely with clients, you will assist in prototyping and piloting AI and machine learning ... patterns, and platform scalability, enabling trusted, value-driven, and compliant data and AI ...
AI Operations Specialist
San Francisco, CA · On-site
$90K - $105K/yr
About Bretton AI Bretton AI is the leading AI agent platform for financial services. Companies like ... Ability to review complex information and identify patterns or issues * Comfortable learning new ...
AI Operations Specialist
San Francisco, CA · On-site
$90K - $105K/yr
About Bretton AI Bretton AI is the leading AI agent platform for financial services. Companies like ... Ability to review complex information and identify patterns or issues * Comfortable learning new ...
A typical market demand pattern is clear: organizations still need entry-level software programmers ... learning engineers . The strongest candidates aren't "tool collectors"-they're people who can show ...
A typical market demand pattern is clear: organizations still need entry-level software programmers ... learning engineers . The strongest candidates aren't "tool collectors"-they're people who can show ...
Patterned Learning Ai information
What are some typical challenges faced by Patterned Learning AI professionals in implementing AI-driven solutions within organizations?
Patterned Learning AI professionals often encounter challenges such as integrating AI models with existing legacy systems, ensuring high-quality and representative training data, and aligning AI solutions with specific business objectives. Collaboration across multidisciplinary teams—including data scientists, software engineers, and business stakeholders—is essential for successful deployment. Additionally, professionals must stay updated on evolving AI technologies and best practices to maintain model accuracy and address ethical considerations.
What are the key skills and qualifications needed to thrive as a Machine Learning Engineer, and why are they important?
To thrive as a Machine Learning Engineer, you need a strong background in mathematics, statistics, programming (especially Python), and a degree in computer science or a related field. Experience with machine learning frameworks such as TensorFlow, PyTorch, and scikit-learn, as well as familiarity with cloud computing platforms and data management tools, is essential. Excellent problem-solving skills, creativity, and clear communication are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies are vital for developing reliable AI systems that solve real-world problems and drive innovation.
What is the difference between Patterned Learning Ai vs Data Scientist?
| Aspect | Patterned Learning Ai | Data Scientist |
|---|---|---|
| Required Credentials | Typically requires machine learning, AI, or computer science degrees; certifications in AI tools | Requires degrees in statistics, computer science, or related fields; often certifications in data analysis |
| Work Environment | Tech companies, AI startups, research labs focusing on AI development | Business, finance, healthcare, and tech sectors analyzing data for insights |
| Employer & Industry Usage | Used by AI-focused organizations developing intelligent systems | Employed across industries for data analysis, predictive modeling, and decision support |
Patterned Learning Ai primarily focuses on developing AI models and algorithms, often requiring specialized technical skills. Data Scientists analyze data to extract insights and inform business decisions. While both roles involve data and machine learning, Patterned Learning Ai is more centered on creating AI systems, whereas Data Scientists interpret data for strategic purposes.
What is Patterned Learning AI?
Patterned Learning AI refers to artificial intelligence systems designed to recognize, learn from, and replicate patterns in data. These systems use algorithms to identify trends, correlations, and structures within large datasets, enabling them to make predictions or automate decision-making processes. Patterned Learning AI is commonly used in fields like image recognition, natural language processing, and predictive analytics. Its applications help businesses and researchers uncover hidden insights, streamline operations, and improve accuracy in various tasks.
What are popular job titles related to Patterned Learning Ai jobs in California? For Patterned Learning Ai jobs in California, the most frequently searched job titles are:
- Remote Senior Machine Learning Engineer
- Remote Machine Learning Engineer
- Temporary Machine Learning R
- Urgently Hiring Machine Learning Engineer New Grad
- Senior Machine Learning Researcher
- Flexible Machine Learning Engineer Biotech
- Deep Learning Engineer
- Machine Learning Engineer
- Machine Engineer
- Volunteer Junior Machine Learning Engineer
What job categories do people searching Patterned Learning Ai jobs in California look for? The top searched job categories for Patterned Learning Ai jobs in California are:
- Amd Machine Learning
- Principal Machine Learning Engineer
- Hourly Remote Machine Learning
- Reinforcement Learning Engineer
- Machine Learning
- Machine Learning Compiler Engineer
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- Contract Apple Machine Learning Engineer
- Freelance Google Machine Learning Engineer
What cities in California are hiring for Patterned Learning Ai jobs? Cities in California with the most Patterned Learning Ai job openings:
Senior/Staff Machine Learning Engineer, General Agents, Enterprise GenAI
Scale AISan Francisco, CA • On-site
Full-time
Posted 2 days ago
Job description
Job Summary:
Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. As a Senior/Staff Machine Learning Engineer on the General Agents team, you’ll design, build, and deploy production-ready AI agents that address high-impact enterprise problems, working across the full agent lifecycle.
Responsibilities:
• Design and implement end-to-end agent systems that combine LLM reasoning, tool use, memory, and control logic to solve recurring enterprise use cases.
• Build scalable, reliable agent architectures that can be deployed across many customers with varying data, tools, and constraints.
• Develop evaluation frameworks, datasets, environments, and metrics to measure agent performance, reliability, and business impact in production settings.
• Collaborate closely with product managers, customers, data annotators, and other engineering teams to translate enterprise requirements into robust agent designs.
• Productionize frontier agent techniques (e.g., planning, multi-step reasoning and tool-use, multi-agent patterns) into maintainable, observable systems.
• Own deployment, monitoring, and iteration of agent systems, including failure analysis and continuous improvement based on real-world usage.
• Contribute to technical direction and architectural decisions for general agent development best practices and methods, with increasing scope and leadership at the Staff level.
Qualifications:
Required:
• 5+ years of experience building and deploying machine learning or AI systems for real-world, production use cases.
• Strong engineering fundamentals, supported by a Bachelor’s and/or Master’s degree in Computer Science, Machine Learning, AI, or equivalent practical experience.
• Deep understanding of modern LLMs, prompt-, context-, and system-level optimization, and agentic system design.
• Proven proficiency in Python, including writing production-quality, testable, and maintainable code.
• Experience building systems that integrate models with external tools, APIs, databases, and services.
• Ability to operate in ambiguous problem spaces, balancing research-driven approaches with pragmatic product constraints.
• Strong communication skills and comfort working in customer-facing or cross-functional environments.
Preferred:
• Hands-on experience building AI agents using modern generative AI stacks (OpenAI APIs, commercial or open-source LLMs).
• Experience with agent frameworks, orchestration layers, or workflow systems (e.g., tool calling, planners, multi-agent setups).
• Familiarity with evaluation, monitoring, and observability for LLM-powered systems in production.
• Experience deploying ML systems in cloud environments and operating them at scale.
• Experience fine-tuning or adapting foundation models using methods like supervised fine-tuning (SFT), reinforcement learning with verifiable rewards (RLVR), and low-rank adaptation (LoRA) to improve agent performance on domain-specific tasks.
• Interest in shaping the future of general-purpose enterprise agents and their real-world impact.
Company:
Scale’s mission is to develop reliable AI systems for the world’s most important decisions. Founded in 2016, the company is headquartered in San Francisco, USA, with a team of 501-1000 employees. The company is currently Late Stage.
Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. As a Senior/Staff Machine Learning Engineer on the General Agents team, you’ll design, build, and deploy production-ready AI agents that address high-impact enterprise problems, working across the full agent lifecycle.
Responsibilities:
• Design and implement end-to-end agent systems that combine LLM reasoning, tool use, memory, and control logic to solve recurring enterprise use cases.
• Build scalable, reliable agent architectures that can be deployed across many customers with varying data, tools, and constraints.
• Develop evaluation frameworks, datasets, environments, and metrics to measure agent performance, reliability, and business impact in production settings.
• Collaborate closely with product managers, customers, data annotators, and other engineering teams to translate enterprise requirements into robust agent designs.
• Productionize frontier agent techniques (e.g., planning, multi-step reasoning and tool-use, multi-agent patterns) into maintainable, observable systems.
• Own deployment, monitoring, and iteration of agent systems, including failure analysis and continuous improvement based on real-world usage.
• Contribute to technical direction and architectural decisions for general agent development best practices and methods, with increasing scope and leadership at the Staff level.
Qualifications:
Required:
• 5+ years of experience building and deploying machine learning or AI systems for real-world, production use cases.
• Strong engineering fundamentals, supported by a Bachelor’s and/or Master’s degree in Computer Science, Machine Learning, AI, or equivalent practical experience.
• Deep understanding of modern LLMs, prompt-, context-, and system-level optimization, and agentic system design.
• Proven proficiency in Python, including writing production-quality, testable, and maintainable code.
• Experience building systems that integrate models with external tools, APIs, databases, and services.
• Ability to operate in ambiguous problem spaces, balancing research-driven approaches with pragmatic product constraints.
• Strong communication skills and comfort working in customer-facing or cross-functional environments.
Preferred:
• Hands-on experience building AI agents using modern generative AI stacks (OpenAI APIs, commercial or open-source LLMs).
• Experience with agent frameworks, orchestration layers, or workflow systems (e.g., tool calling, planners, multi-agent setups).
• Familiarity with evaluation, monitoring, and observability for LLM-powered systems in production.
• Experience deploying ML systems in cloud environments and operating them at scale.
• Experience fine-tuning or adapting foundation models using methods like supervised fine-tuning (SFT), reinforcement learning with verifiable rewards (RLVR), and low-rank adaptation (LoRA) to improve agent performance on domain-specific tasks.
• Interest in shaping the future of general-purpose enterprise agents and their real-world impact.
Company:
Scale’s mission is to develop reliable AI systems for the world’s most important decisions. Founded in 2016, the company is headquartered in San Francisco, USA, with a team of 501-1000 employees. The company is currently Late Stage.
About Scale AI
Sourced by ZipRecruiter
Industry
Software development
Company size
201 - 500 Employees
Headquarters location
San Francisco, CA, US
Year founded
2016