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Patterned Learning Ai Jobs in California (NOW HIRING)

What You'll Do * Build AI-powered systems that improve the quality, reliability, and customer ... learning from operational patterns to prevent recurring failures, and providing real-time ...

About Eightfold Eightfold is a global leader in AI-native enterprise talent platform, trusted by ... Understanding of distributed system design patterns and microservices architecture. * Demonstrable ...

What You'll Do * Build AI-powered systems that improve the quality, reliability, and customer ... learning from operational patterns to prevent recurring failures, and providing real-time ...

AI Consultant

Foster City, CA · On-site

$100 - $125/hr

Emphasis is on speed, usability, and learning not production hardening. Agentic Experimentation ... Exposure to agent-based AI patterns or evaluation frameworks. Basic understanding of orchestration ...

Machine Learning Engineer, AI New York, NY (Hybrid) Biohub is the first large-scale initiative ... Define and shape the engineering patterns your team and collaborating researchers will build on for ...

Company Description PatternAI is an automated machine learning platform that reveals critical patterns in data for narrow business problems. We're seeking an outstanding ML Engineer to join our data ...

Company Description PatternAI is an automated machine learning platform that reveals critical patterns in data for narrow business problems. We're seeking an outstanding ML Engineer to join our data ...

Applied AI Engineer

San Francisco, CA · On-site

$160K - $190K/yr

... learning models for performance, scalability, and accuracy in production environments. * Implement Retrieval-Augmented Generation (RAG) pipelines, AI agentic patterns, and multi-modal model ...

Applied AI Engineer

Santa Clara, CA · On-site

$160K - $190K/yr

... learning models for performance, scalability, and accuracy in production environments. * Implement Retrieval-Augmented Generation (RAG) pipelines, AI agentic patterns, and multi-modal model ...

Applied AI Engineer

San Francisco, CA · On-site

$160K - $190K/yr

... learning models for performance, scalability, and accuracy in production environments. * Implement Retrieval-Augmented Generation (RAG) pipelines, AI agentic patterns, and multi-modal model ...

Applied AI Engineer

Santa Clara, CA · On-site

$160K - $190K/yr

... learning models for performance, scalability, and accuracy in production environments. * Implement Retrieval-Augmented Generation (RAG) pipelines, AI agentic patterns, and multi-modal model ...

... learning models for performance, scalability, and accuracy in production environments. * Implement Retrieval-Augmented Generation (RAG) pipelines, AI agentic patterns, and multi-modal model ...

Applied AI Engineer

Irvine, CA · On-site

$160K - $190K/yr

... learning models for performance, scalability, and accuracy in production environments. * Implement Retrieval-Augmented Generation (RAG) pipelines, AI agentic patterns, and multi-modal model ...

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Showing results 1-20

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?

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 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 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 June 2026, with employment types broken down into 53% Full Time, 45% Part Time, and 2% Contract. Highlights an 66% Physical, 4% Hybrid, and 30% Remote job distribution.
Machine Learning Engineer

Machine Learning Engineer

Adobe

San Jose, CA

Full-time

Posted 10 days ago


Job description

The Opportunity

Adobe Journey Optimizer (AJO) powers personalized, real-time customer experiences at massive scale for global brands. Our Reliability Engineering & Operational Intelligence (REOI) team is building AJO's autonomous operating system - an AI-native platform that proactively improves product quality, accelerates issue resolution, and enhances customer experience through intelligent automation and continuous learning.

We are seeking a Machine Learning Engineer who is eager to apply ML and AI to solve real challenges in reliability, quality, and operational intelligence at scale. In this role, you will build AI systems that make AJO progressively more reliable and self-healing - learning from every incident, preventing recurring failures, and ensuring exceptional customer experiences while enabling the platform to scale 4x without scaling operational overhead.
This is a unique opportunity to work at the intersection of production systems, AI/ML, and product quality - where your work directly impacts how millions of customer journeys are delivered reliably every day.
What You'll Do
  • Build AI-powered systems that improve the quality, reliability, and customer experience of AJO - by automating issue detection and resolution with human-in-the-loop approval, learning from operational patterns to prevent recurring failures, and providing real-time visibility into customer health and platform stability
  • Develop intelligent knowledge systems that compound expertise over time - using vector embeddings, similarity retrieval, and pattern clustering to ensure every incident investigation builds on past learnings, making the platform progressively smarter and more self-healing
  • Design and implement LLM-based workflows using prompt engineering, structured outputs, tool calling, and agentic reasoning patterns to create autonomous capabilities that operate safely at production scale
  • Build evaluation frameworks to measure AI system performance: quality improvement rates, automation success rates, mean time to resolution (MTTR) reduction, and customer impact metrics
  • Integrate AI capabilities with production infrastructure: Kubernetes, Prometheus, Splunk, GitHub, and 30+ operational data sources - creating closed-loop systems that detect, learn, and act autonomously
  • Apply ML techniques to operational data: anomaly detection for early issue detection, time-series forecasting for capacity planning, pattern clustering for recurring failure identification, and predictive analysis for proactive prevention
  • Collaborate with SREs, software engineers, and product teams to understand quality and reliability challenges, then design and deploy AI solutions that address them systematically
  • Contribute to code reviews, testing, documentation, and CI/CD pipelines - building production-grade ML systems with the same rigor as mission-critical infrastructure

What You Need to Succeed
  • BS/MS in Computer Science, Machine Learning, Data Science, or related field, with 2-4 years of professional experience (or strong academic/internship experience in ML/AI applied to real-world problems)
  • Hands-on experience with Python and ML frameworks: scikit-learn, PyTorch, TensorFlow, HuggingFace, or LangChain
  • Practical knowledge of LLM APIs (OpenAI, Anthropic Claude, Azure OpenAI) and prompt engineering techniques for building agentic workflows
  • Understanding of vector databases and similarity search (FAISS, Pinecone, ChromaDB, MongoDB Atlas Vector Search, or similar)
  • Foundational knowledge of ML concepts: embeddings, clustering, classification, evaluation metrics (precision/recall/F1), and model deployment best practices
  • Comfortable building APIs and integrating ML models into backend services using FastAPI, Flask, or similar frameworks
  • Eagerness to learn production ML operations: model monitoring, A/B testing, continuous evaluation, and safety guardrails for AI systems
  • Strong problem-solving skills, attention to detail, and the ability to iterate quickly based on data and feedback
  • Excellent communication and collaboration - able to explain ML concepts to non-ML engineers and translate business requirements into technical solutions
  • Bonus: Experience with Kubernetes, observability tools (Prometheus, Grafana, Datadog), incident management systems, or building AI agents for operational use cases

About Adobe

Adobe empowers everyone to create through innovative platforms and tools that unleash creativity, productivity and personalized customer experiences. Adobe's industry-leading offerings including Adobe Acrobat Studio, Adobe Express, Adobe Firefly, Creative Cloud, Adobe Experience Platform, Adobe Experience Manager, and GenStudio enable people and businesses to turn ideas into impact, powered by AI and driven by human ingenuity.

Our 30,000+ employees worldwide are creating the future and raising the bar as we drive the next decade of growth. We're on a mission to hire the very best and believe in creating a company culture where all employees are empowered to make an impact. At Adobe, we believe that great ideas can come from anywhere in the organization. The next big idea could be yours.


Let's Adobe together

At Adobe, we believe in creating a company culture where all employees are empowered to make an impact. Learn more about Adobe life, including our values and culture, focus on people, purpose and community, Adobe for All, comprehensive benefits programs, the stories we tell, the customers we serve, and how you can help us advance our mission of empowering everyone to create.

Adobe is proud to be an Equal Employment Opportunity employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other protected characteristic. Learn more.

Adobe aims to make our Careers website and recruiting process accessible to any and all users. If you have a disability or special need that requires accommodation to navigate our website or complete the application process, email accommodations@adobe.com or call +1 408-536-3015.

AI Use Guidelines for Interviews:
Our interviews are designed to reflect your own skills and thinking. The use of AI or recording tools during live interviews is not permitted unless explicitly invited by the interviewer or approved in advance as part of a reasonable accommodation. If these tools are used inappropriately or in a way that misrepresents your work, your application may not move forward in the process.

At Adobe, we empower employees to innovate with AI - and we look for candidates eager to do the same. As part of the hiring experience, we provide clear guidance on where AI is encouraged during the process and where it's restricted during live interviews. See how we think about AI in the hiring experience.

Expected Pay Range:

Our compensation reflects the cost of labor across several U.S. geographic markets, and we pay differently based on those defined markets. The U.S. pay range for this positionis $102,400 -- $202,250 annually. Paywithin this range varies by work locationand may also depend on job-related knowledge, skills,and experience. Your recruiter can share more about the specific salary range for the job location during the hiring process. In California, the pay range for this position is $139,700 - $202,250

At Adobe, for sales roles starting salaries are expressed as total target compensation (TTC = base + commission), and short-term incentives are in the form of sales commission plans. Non-sales roles starting salaries are expressed as base salary and short-term incentives are in the form of the Annual Incentive Plan (AIP).

In addition, certain roles may be eligible for long-term incentives in the form of a new hire equity award.

State-Specific Notices:

California:

Fair Chance Ordinances

Adobe will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and "fair chance" ordinances.

Colorado:

Application Window Notice

If this role is open to hiring in Colorado (as listed on the job posting), the application window will remain open until at least the date and time stated above in Pacific Time, in compliance with Colorado pay transparency regulations. If this role does not have Colorado listed as a hiring location, no specific application window applies, and the posting may close at any time based on hiring needs.

Massachusetts:

Massachusetts Legal Notice

It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.


Adobe logo

About Adobe

Sourced by ZipRecruiter

Adobe for All is our vision to advance diversity, equity, and inclusion (DEI) across our company and in our communities. We’re focused on creating a more diverse and inclusive workforce; unleashing the full potential of every employee; and driving meaningful impact for Adobe, our industry, and society at large. Creativity has the power to unite us and inspire us to change the world. Through a vision we call Creativity for All, we’re empowering millions of people of all ages and backgrounds to express themselves, reach their full potential, and share their diverse perspectives with the world. We’re committed to advancing the responsible use of technology and driving a positive environmental impact through sustainability and climate action. Our innovations are making a significant impact across AI ethics, security, privacy, trust and safety, accessibility, and sustainability.

Industry

Computer and computer peripheral equipment and software wholesalers

Company size

10,000+ Employees

Headquarters location

San Jose, CA, US

Year founded

1982