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Patterned Learning Ai Jobs in California (NOW HIRING)

... patterns and production AI discipline. Qualifications To be successful in this role you have: * 6+ ... Published work, patents, or open-source contributions in Machine Learning, AI, distributed systems ...

... patterns and production AI discipline. Qualifications To be successful in this role you have: * 6+ ... Published work, patents, or open-source contributions in Machine Learning, AI, distributed systems ...

... patterns and production AI discipline. Qualifications To be successful in this role you have: * 6+ ... Published work, patents, or open-source contributions in Machine Learning, AI, distributed systems ...

Nace AI is a company focused on leveraging machine learning to drive product value. They are ... design patterns). • BS degree in CS or related technical field. • Solid Experience with ML ...

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 ...

Nace AI is a company focused on machine learning solutions, and they are seeking a Machine Learning ... design patterns). • BS degree in CS or related technical field. • Solid Experience with ML ...

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 ...

Showing results 21-40

Patterned Learning Ai information

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 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?

AspectPatterned Learning AiData Scientist
Required CredentialsTypically requires machine learning, AI, or computer science degrees; certifications in AI toolsRequires degrees in statistics, computer science, or related fields; often certifications in data analysis
Work EnvironmentTech companies, AI startups, research labs focusing on AI developmentBusiness, finance, healthcare, and tech sectors analyzing data for insights
Employer & Industry UsageUsed by AI-focused organizations developing intelligent systemsEmployed 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 cities in California are hiring for Patterned Learning Ai jobs?

Cities in California with the most Patterned Learning Ai job openings:

Infographic showing various Patterned Learning Ai job openings in California as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 23% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Staff Machine Learning Engineer

ServiceNow

Santa Clara, CA • On-site

$176K - $308K/yr

Full-time

Medical, Retirement

Posted 19 days ago


ServiceNow rating

8.3

Company rating: 8.3 out of 10

Based on 10 frontline employees who took The Breakroom Quiz

99th of 247 rated software companies


Job description

Company Description

It all started when engineer Fred Luddy wrote code that automated a tedious task for his coworker, Phyllis. She cried tears of joy. That moment inspired Fred to build a company that could do that for everyone—freeing people from busywork so they could focus on meaningful work. Today, ServiceNow is the AI control tower for business reinvention. Our ServiceNow AI platform brings together any AI, any data, and any workflow— helping 85% of the Fortune 500® work smarter, faster, and better. We're building an AI-native culture where technology and talent are unstoppable together. And we're just getting started.

Join us to put AI to work for people.

Job Description

About the Team

The Agentic Engineering organization at ServiceNow is the customer-obsessed engineering group that builds a conversational AI experience that turns enterprise intent into completed work. We advance how enterprise AI reasons, remembers, and executes.

The Agent Orchestration team — the team you'll join — owns the execution core: the agent harness, orchestration runtime, multi-agent coordination, memory management, and the evaluation frameworks that ensure agents behave correctly in production. Every autonomous action Otto promises depends on what this team ships.

By joining our team, you’ll be at the forefront of our AI transformation journey, backed by the global scale of ServiceNow and the agility of a high-growth environment. We are looking for world-class talent to help us extend agentic AI to every employee across every corner of the business

You will design, build, and operate production-grade agentic AI systems embedded across ServiceNow's platform — autonomous agents that reason over real enterprise data, take action across workflows, and run safely at Fortune 500 scale. 

Your core focus areas: 

  • Agentic architecture. Design and ship multi-agent systems — orchestration, tool use, planning loops, memory, and failure recovery — that operate reliably in production, not in notebooks. 
  • Enterprise-grounded reasoning. Build agents that leverage ServiceNow's data layer — CMDB, Workflow Data Fabric, and Knowledge Graph — to make decisions with context no frontier model has on its own. 
  • Trust, safety, and governance. Own the guardrails: observability, human-in-the-loop controls, and compliance infrastructure that make autonomous systems safe to deploy at scale. 
  • Retrieval and grounding. Work closely with our search team to ensure agents are grounded in accurate, low-latency retrieval — RAG pipelines, hybrid search, re-ranking, and evaluation — as a critical dependency of agentic quality. 
  • Model integration and evaluation. Integrate frontier models (Anthropic, Google, OpenAI) into the Sense → Decide → Act → Govern architecture; evaluate trade-offs across cost, latency, and capability for production use cases. 
  • Engineering leadership. Raise the technical bar through architecture decisions, code reviews, and coaching — particularly on agentic design patterns and production AI discipline. 
Qualifications

To be successful in this role you have:

  • 6+ years building production software systems with a strong track record on reliability, performance, and scalability
  • Hands-on experience shipping generative AI products — not just integrating LLM APIs or building prototypes, but owning AI-powered features that production users depend on
  • Solid depth in how large language models work: failure modes, context constraints, and how prompt design shapes model behavior at scale
  • Practical prompt engineering experience: systematically designing, versioning, and evaluating prompts across model updates or A/B evaluation cycles
  • A real track record in eval engineering — not just familiarity, but a portfolio of evaluation suites designed, shipped, and used to drive quality decisions in production AI systems
  • Cost and efficiency awareness at the system level: experience reasoning about model routing, inference cost, and latency tradeoffs in production
  • Strong software engineering fundamentals: distributed systems, API design, and testing discipline
  • Comfort operating in fast-moving, ambiguous, startup-like AI product environments

Nice to Have

  • Exposure to AI services deployed in a micro services-based architecture (Kubernetes, OpenShift, etc.)
  • Experience tracing, debugging, identifying root causes, and resolving issues in AI codebases that span multiple services, multiple environments, and/or multiple tenants
  • Published work, patents, or open-source contributions in Machine Learning, AI, distributed systems, etc.

For positions in this location, we offer a base pay of $176,100 - $308,200, plus equity (when applicable), variable/incentive compensation and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the base pay shown is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location. We also offer health plans, including flexible spending accounts, a 401(k) Plan with company match, ESPP, matching donations, a flexible time away plan and family leave programs. Compensation is based on the geographic location in which the role is located and is subject to change based on work location.


Additional Information

Work Personas

We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here. To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service.

Equal Opportunity Employer

ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, gender identity,  veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements.  

Accommodations

We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact globaltalentss@servicenow.com for assistance. 

Export Control Regulations

For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities. 

From Fortune. ©2026 Fortune Media IP Limited. All rights reserved. Used under license.


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About ServiceNow

Sourced by ZipRecruiter

At ServiceNow, our technology makes the world work for everyone, and our people make it possible. We move fast because the world can't wait, and we innovate in ways no one else can for our customers and communities. By joining ServiceNow, you are part of an ambitious team of change makers who have a restless curiosity and a drive for ingenuity. We know that your best work happens when you live your best life and share your unique talents, so we do everything we can to make that possible. We dream big together, supporting each other to make our individual and collective dreams come true. The future is ours, and it starts with you. With more than 7,400+ customers, we serve approximately 80% of the Fortune 500, and we're proud to be one of FORTUNE's 100 Best Companies to Work For® and World's Most Admired Companies® 2022.

Industry

It services

Company size

5,001 - 10,000 Employees

Headquarters location

Santa Clara, CA, US

Year founded

2004