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Patterned Learning Ai Jobs in Pennsylvania (NOW HIRING)

SEI Investments

AI Cybersecurity Engineer

Oaks, PA · On-site

... attack patterns. * Engineer AI-powered security detection systems leveraging machine learning for threat hunting, anomaly detection, and behavioral analytics. Cross-Functional Collaboration ...

Comcast

Engineer 6, Machine Learning, Data & AI

Philadelphia, PA · On-site +1

$115K - $138K/yr

The successful candidate will define the architecture, standards, and engineering patterns that ... Experience supporting AI, machine learning, advanced analytics, or data modernization initiatives.

Posted today

Comcast

Engineer 6, Machine Learning, Data & AI

West Chester, PA · On-site +1

$108K - $130K/yr

The successful candidate will define the architecture, standards, and engineering patterns that ... Experience supporting AI, machine learning, advanced analytics, or data modernization initiatives.

Posted today

Tata Consultancy Service Limited

AI Modeler

Malvern, PA · On-site

$140K - $160K/yr

... patterns: ground truth datasets, accuracy measurement, regression testing for model outputs • ... machine learning to Amazon Bedrock Foundation Models. The work directly impacts operational ...

The Pennsylvania State University

Apply sound software engineering and design patterns when integrating AI-assisted capabilities ... The Data Empowered Learning team is primarily located on campus at University Park, and this ...

TekShapers

SR. AI Engineer with Snowflake

Oaks, PA · On-site

$106K - $146K/yr

... analysis patterns. Hands-on experience with Microsoft Azure cloud platform and AI services ... Experience with Azure OpenAI, Azure AI Foundry / AI Studio, Azure Machine Learning, Cognitive ...

Coforge

AI Architect

Phoenixville, PA · On-site

Lead design, development, deployment, and lifecycle management of AI and machine learning solutions ... patterns. * Azure: practical experience with Azure OpenAI/Models, Azure AI Search, Azure ML, AKS ...

hajoca

AI Enablement Lead

Lafayette Hill, PA

Document repeatable patterns, standards, and playbooks that improve the consistency and scalability ... Partner with the Learning Center team and Marketing & Communications to develop and distribute ...

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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 are popular job titles related to Patterned Learning Ai jobs in Pennsylvania? For Patterned Learning Ai jobs in Pennsylvania, the most frequently searched job titles are:
What job categories do people searching Patterned Learning Ai jobs in Pennsylvania look for? The top searched job categories for Patterned Learning Ai jobs in Pennsylvania are:
What cities in Pennsylvania are hiring for Patterned Learning Ai jobs? Cities in Pennsylvania with the most Patterned Learning Ai job openings:
Patterned Learning Ai jobs near you
Infographic showing various Patterned Learning Ai job openings in Pennsylvania as of August 2026, with employment types broken down into 1% As Needed, 70% Full Time, 25% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

AI Safety Engineer (Red Teaming) - Remote

micro1 AI

Philadelphia, PA • Remote

$50 - $90/hr

Part-time

This job post has expired today. Applications are no longer accepted.

Job description

Role Title: AI Jailbreak & Prompt-Injection Security Expert


Role Type: Contractor


Location: Remote


micro1 is engaging AI Jailbreak & Prompt-Injection Security Experts to contribute to a cutting-edge customer initiative focused on AI safety and robustness. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Scope of Work

  1. Design and implement advanced methodologies for evaluating AI system safety, focusing on ethical jailbreaks, LLM red teaming, prompt injection, and tool-use abuse scenarios.
  2. Create comprehensive cross-domain elicitation strategies to uncover multi-turn and complex adversarial bypass patterns in AI models.
  3. Develop, maintain, and update regression test suites that systematically test for jailbreak susceptibility and prompt-injection vulnerabilities.
  4. Construct robust evaluation frameworks that stress-test AI models against real-world adversarial threats, aiming to enhance overall system robustness.
  5. Collaborate with technical stakeholders to translate security findings into actionable improvements for model safety and risk mitigation.
  6. Document methodologies, findings, and best practices in clear, well-structured written reports and presentations for both technical and non-technical audiences.


Preferred Qualifications

  1. 2+ years of expertise in adversarial machine learning, LLM red teaming, AI safety evaluation, or a closely related security domain
  2. Proven experience researching, testing, or uncovering vulnerabilities related to ethical jailbreaks, prompt injection, tool-use abuse, or adversarial AI attacks.
  3. Advanced degree (PhD, MS) in computer science, cybersecurity, machine learning, or a relevant discipline, or equivalent operational/professional background.
  4. High credibility and recognition within the AI security or adversarial ML community—such as published research, open-source tools, or conference presentations.
  5. Exceptional written and verbal communication skills, with a strong focus on clear documentation and collaborative problem-solving.
  6. Prior participation in multi-disciplinary projects or cross-functional AI safety initiatives is a plus.
  7. Familiarity with current LLM architectures, prompt engineering techniques, and security assessment tools is highly desirable.

Apply