Staff Writer jobs

Essential Responsibilities:

• Develop clear objectives and priorities within content design to deliver results and meet organizational goals
• Influence decision-making at the senior leadership level
• Perform the most highly complex work assignments using domain knowledge and extensive business expertise
• Develop and deliver innovative content design strategies that enhance user experience and benefit customers and/or clients
• Lead major business projects which impact the content design unit or the product function
• Design, evaluate, and select process, product, and service improvements based on thorough understanding of business needs and industry trends

Expected Qualifications:

• 8+ years relevant experience and a Bachelor’s degree OR Any equivalent combination of education and experience.

Travel Percent:

The total compensation for this practice may include an annual performance bonus (or other incentive compensation, as applicable), equity, and medical, dental, vision, and other benefits. For more information, visit .

Our Benefits:

Any general requests for consideration of your skills, please

Essential Responsibilities:

• Develop and optimize machine learning models for various applications.
• Preprocess and analyze large datasets to extract meaningful insights.
• Deploy ML solutions into production environments using appropriate tools and frameworks.
• Collaborate with cross-functional teams to integrate ML models into products and services.
• Monitor and evaluate the performance of deployed models.

Expected Qualifications:

• 3+ years relevant experience and a Bachelor’s degree OR Any equivalent combination of education and experience.
• Experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn.
• Familiarity with cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment.
• Several years of experience in designing, implementing, and deploying machine learning models.

Key Responsibilities:

• Research and develop large-scale foundation models, including continuous pre-training, supervised fine-tuning, and alignment techniques

• Design novel architectures and training methodologies for domain-specific language models in financial services

• Build scalable ML pipelines for foundation model training, evaluation, and deployment at enterprise scale

• Conduct rigorous experimentation and benchmarking to ensure model quality, safety, and performance

• Deploy foundation models into production environments to drive business insights and enhance customer experiences

• Collaborate with cross-functional teams to identify high-impact use cases and translate research into practical solutions

• Stay current with latest developments in LLM and LLM-Agent research and contribute to the broader AI/ML community through publications and open-source contributions

• Mentor junior researchers and contribute to technical strategy for foundation model initiatives

Preferred Qualifications:

• PhD in Computer Science, Machine Learning, AI, or related field with focus on large language models and LLM Agent

• 1-3+ years of hands-on experience training and deploying large-scale language models (7B+ parameters)

• Deep expertise in transformer architectures, attention mechanisms, and modern training techniques

• Experience with distributed training frameworks (PyTorch, JAX, DeepSpeed, etc.)

• Strong background in NLP, deep learning, and statistical machine learning

• Proven track record of research publications in top-tier venues (NeurIPS, ICML, ACL, etc.)

Travel Percent:

The total compensation for this practice may include an annual performance bonus (or other incentive compensation, as applicable), equity, and medical, dental, vision, and other benefits. For more information, visit .

Our Benefits:

Any general requests for consideration of your skills, please

Essential Responsibilities:

• Acts as a project or system leader, coordinating the activities of other engineers on the project or within the system
• Determines the technical tasks that other engineers will follow
• Actions result in the achievement of customer, operational, program or service objectives
• Proactively improves existing structures & processes
• Exercises judgement in reconciling diverse and competing priorities (time, quality, complexity risk) to identify optimal solutions to problems
• Notices patterns and condenses repetition into densely meaningful generalized solutions
• Collaborates with management to set/improve standards for engineering rigor
• Trusted to represent PayPal, Inc to the outside world via interactions with partners, customers, or industry organizations

Expected Qualifications:

• 5+ years relevant experience and a Bachelor’s degree OR Any equivalent combination of education and experience.

• Experience in Spring boot and other frameworks in Java or python
• Experience in UI stack such as react or other
• Experience with large-scale, high-performance systems.
• Experience in running large scale CI/CD pipelines using Jenkins, Github or Harness
• Experience with cloud platforms (AWS, GCP, Azure).

Travel Percent:

The total compensation for this practice may include an annual performance bonus (or other incentive compensation, as applicable), equity, and medical, dental, vision, and other benefits. For more information, visit .

Our Benefits:

Any general requests for consideration of your skills, please

Essential Responsibilities:

• Lead the development and optimization of advanced machine learning models.
• Oversee the preprocessing and analysis of large datasets.
• Deploy and maintain ML solutions in production environments.
• Collaborate with cross-functional teams to integrate ML models into products and services.
• Monitor and evaluate the performance of deployed models, making necessary adjustments.

Expected Qualifications:

• 5+ years relevant experience and a Bachelor’s degree OR Any equivalent combination of education and experience.
• Extensive experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn.
• Expertise in cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment.

Travel Percent:

The total compensation for this practice may include an annual performance bonus (or other incentive compensation, as applicable), equity, and medical, dental, vision, and other benefits. For more information, visit .

Our Benefits:

Any general requests for consideration of your skills, please

Being the cybersecurity partner of choice, protecting our digital way of life.

Your Career

As a Principal AI Engineer for the Enterprise AI Platform, you will be a pivotal technical leader driving the identification, design, and hands-on implementation of AI-powered solutions that directly address critical business challenges across IT and all enterprise functions (Sales, Marketing, Finance, HR, Legal, etc.). You will operate where AI innovation, top-tier engineering, and significant business outcomes converge, acting as the technical bridge between complex business problems and cutting-edge AI execution. Leveraging our robust Enterprise AI Platform, you will translate ambiguous problems into concrete AI solution designs, build core components of these solutions, and ensure their successful deployment and measurable impact, supporting both code-based and low-code/no-code approaches.

Your Impact

• Applied AI Solution Design & Architecture: Deeply understand complex business problems and strategic objectives across various enterprise functions. Break down ambiguous AI problems into concrete, actionable AI solution designs, including identifying the appropriate AI models, data requirements, and integration points for end-to-end AI applications
• Hands-on Development & Implementation: Lead the hands-on development and implementation of key components of the AI assistant, agent, app, supporting both traditional and Generative AI model development, deployment, and real-time inference systems. Drive the successful integration of experimental AI technologies into production, showcasing tangible business value through rapid prototyping and measurable results
• System Design & Optimization: Contribute significantly to the detailed design of large-scale, distributed AI/ML systems, ensuring performance, reliability, security, and developer-friendliness. Optimize existing systems for scalability, efficiency, and maintainability, ensuring the platform's ability to handle massive scale data and inference requests, optimizing for low latency and high throughput for real-time AI applications
• Rapid Experimentation & Integration: Evaluate and integrate new AI tools, frameworks, SDKs, and cloud solutions into the platform, ensuring alignment with architectural strategy and engineering needs. Lead proof-of-concepts (POCs) for emerging AI innovations and drive their integration into production through long-term architectural evolution
• Architectural Adherence & Best Practices: Champion and enforce design standards, patterns, and best practices for scalable and secure development of AI assistants, agents, and applications across various teams
• Technical Leadership & Mentorship: Provide technical leadership and mentorship to other AI and ML engineers, fostering a culture of engineering excellence, innovation, and hands-on experimentation within the team and across the company
• Cross-Functional Collaboration: Partner effectively with executive leadership, data science teams, engineering, product stakeholders, and business leaders to translate complex business use-cases into scalable, production-grade AI solutions. Act as a go-to expert for complex AI engineering challenges, providing technical guidance and hands-on support
• Responsible AI & Governance: Implement features and practices that ensure AI systems comply with responsible AI principles, data governance, privacy laws, security policies, and ethical AI frameworks.
• Innovation & Research: Actively learn and incorporate advances in Agents, Generative AI, LLMs, and scalable AI architectures. Actively research and evaluate cutting-edge AI/ML techniques, algorithms, and models (e.g., foundation models, multi-modal AI) to identify opportunities for platform enhancement and new solution development
• MLOps and Automation: Lead the implementation and continuous improvement of MLOps pipelines, including automated model training, versioning, deployment, and monitoring, to streamline the AI lifecycle. Design and implement automated testing strategies for AI models and platform components to ensure model quality, robustness, and drift detection

Your Experience

• 10+ years of experience in software engineering, distributed systems, or enterprise architecture, including at least 5 years focused on leading AI/ML engineering or platform development
• Proven expertise in designing and building complex, enterprise-grade AI/ML platforms and applications, ideally across multiple domains (e.g., customer support, finance, sales)
• Deep practical understanding of the full AI lifecycle for developing assistants, agents, and applications, including feature engineering, RAGs, model training, evaluation, validation, deployment, and monitoring
• Extensive hands-on experience with distributed systems architecture, streaming data platforms, data lakes, and real-time decision engines
• Generative AI & Large Language Models (LLMs): Direct hands-on experience with Generative AI technologies, including Large Language Models (LLMs), multi-modal models, RAGs (Retrieval-Augmented Generation), and agentic AI systems. Familiarity with techniques for LLM alignment, fine-tuning, and responsible deployment
• Proficiency in modern AI/ML frameworks (e.g., TensorFlow, PyTorch, JAX) and cloud AI/ML platforms (e.g., AWS SageMaker, Google Cloud AI Platform/Vertex AI, Azure ML)
• Strong programming skills in languages such as Python, Java, or Go
• Excellent communication skills with a track record of influencing technical and cross-functional stakeholders at VP+ levels
• System-Level Thinking: Demonstrated ability to think at a system level, understanding complex interdependencies within distributed AI architectures and optimizing end-to-end performance

Preferred Qualifications

• Master's degree or Ph.D. in Computer Science, Machine Learning, or a related technical field or equivalent military experience required
• Experience contributing to open-source AI projects or publications in top-tier AI conferences
• Prior experience in a technical consulting or solutions architecture role, bridging technical teams and senior business stakeholders
• Deep understanding of cybersecurity principles as they apply to AI systems

Compensation Disclosure

The compensation offered for this position will depend on qualifications, experience, and work location. For candidates who receive an offer at the posted level, the starting base salary (for non-sales roles) or base salary + commission target (for sales/commissioned roles) is expected to be between $179000/YR - $290500/YR. The offered compensation may also include restricted stock units and a bonus. A description of our employee benefits may be found .

All your information will be kept confidential according to EEO guidelines.

Being the cybersecurity partner of choice, protecting our digital way of life.

Your Career

Threat Detection Engineer (Threat Data Platform)

Your Impact

• This role bridges security research and fundamental software implementation

• You will be responsible as subject matter experts to interpret threat intelligence from both automated systems and machine learning.

• You will also be creating the software modules that generate indicator lists, measure indicator quality, and gauge the quality of intelligence ingested.

• The Threat Data Platform is the keystone for intelligence production and dissemination; you are its steward

Your Experience

• Demonstrable expertise in an operational security role - soc analysis, reverse engineering, threat intelligence monitoring and/or creation

• Experience interpreting logs from commercial security products

• Deep understanding of sandbox technologies; how they work and interpreting their reports

• Passion for using automation to enable workflows and automate your day to day tasks

• Expert experience in python is a must

• Strong understanding of fundamental software design for data access and processing larger datasets (REST/SQL/BQ/Mongo/etc…)

Compensation Disclosure

The compensation offered for this position will depend on qualifications, experience, and work location. For candidates who receive an offer at the posted level, the starting base salary (for non-sales roles) or base salary + commission target (for sales/commissioned roles) is expected to be between $149,000 - $204,000/YR. The offered compensation may also include restricted stock units and a bonus. A description of our employee benefits may be found .

All your information will be kept confidential according to EEO guidelines.

Essential Responsibilities:

• Acts as a project or system leader, coordinating the activities of other engineers on the project or within the system

• Determines the technical tasks that other engineers will follow

• Actions result in the achievement of customer, operational, program or service objectives

• Proactively improves existing structures & processes

• Exercises judgement in reconciling diverse and competing priorities (time, quality, complexity risk) to identify optimal solutions to problems

• Notices patterns and condenses repetition into densely meaningful generalized solutions

• Collaborates with management to set/improve standards for engineering rigor

• Trusted to represent PayPal, Inc to the outside world via interactions with partners, customers, or industry organizations

Expected Qualifications:

• Minimum of 8 years of relevant work experience and a Bachelor's degree or equivalent experience.

The total compensation for this position may include an annual performance bonus (or other incentive compensation, as applicable), equity, and medical, dental, vision, and other benefits. For more information, visit

The U.S. national annual pay range for this role is $to $

Our Benefits:

Any general requests for consideration of your skills, please