United States, California, Survey Researcher jobs

As an Sr. Applied Research technical lead at eBay, you will be at the center of how multi-modal intelligence is applied across products. You will not just support AI development, you will lead a team of applied researchers and machine learning engineers to help define how AI driven solutions operate, scale, and deliver value. Your work will directly influence model quality, operational efficiency, and the ways AI enhances user experience across eBay.

Metrics and Reporting:

Define key performance metrics for AI models. Maintain operational excellence standards for data pipelines and models in production

Tools and Technical Fluency

Ph.D. in AI or equivalent research experience. Proficiency in Python and PyTorch for data processing, model training and inference. Expertise in Vision-Language Models and image/video retrieval. Deep understanding of key computer vision techniques for classification, image/video retrieval, 3D modeling, and Image/Video generation. Bonus: experience with frameworks for large-scale multi-GPU training (e.g. PyTorch Lightening, Nemo etc.) and for large scale inference (TensorRT, vLLM )

Two years plus of experience as a tech lead or a manager of science/engineering teams. Comfortable coaching, and enabling team members to deliver high-quality work through clear direction, support, and collaboration.

Quality and Attention to Detail
Detail oriented in how you work with data, models, documentation, and process. Ability to catch inconsistencies early, ensuring standards are consistently met across workflows and deliverables.

The base pay range for this position is expected in the range below:

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

Your Impact

As a Principal Threat Intelligence Researcher in the Intel Response Unit, your primary responsibilities will include:

1. Client-facing Briefing: Deliver fused intelligence insights on a recurring basis to clients across industry verticals focusing on relevant cyber threat activities, trends, and shifts in the cyber threat landscape trends. Custom tailored content should empower defensive actions for clients, providing their threat intelligence and security teams with key observations, insights, and perspective. Content creation will require performing independent research across internal data sets, commercial third party data, and open sources. This will also include leveraging existing Unit 42 intelligence publications and working with partners from internal intelligence teams.

2. Client-facing RFI Support: Provide tailored research and analysis for client-based RFIs to drive business and security outcomes. Leverage the full weight of Palo Alto Network's unique data holdings, on-going research, cross-company capabilities, and externally sourced information. Assist leadership in creating a scalable solution to service multiple industries and similar stakeholder types. Model research findings into Unit 42’s Threat Intelligence Knowledge Repository (TIKR). Provide recommendations and help implement improvements to service support quality and speed to enhance the effectiveness and differentiation of our threat intelligence services. Some requests will require rapid turn around time, which may include operating outside of normal business hours.

3. Threat Profile Production: Create cyber threat profiles for clients to identify top cyber threat activities, groups, and trends relevant to a client’s unique business operations then provide tailored defensive recommendations. Work with clients to understand their operational footprint, business objectives, technology and security stacks, and areas of risk exposure. Develop MITRE ATT&CK workflows and heatmaps for top threat groups.

4. Anticipatory Threat Knowledge Creation: Develop structured intelligence insights tracking adversary trends, motivations, organizational priorities, and historical region and industry targeting patterns. This information will act as a backdrop to support intelligence production response for unfolding cyber events, exploitation trends, and threat actor campaigns. Collaborate with other Unit 42 CTI SMEs in fusion cells to expand research and existing collateral on threat groups.

5. Industry Voice & Expertise: Must be willing to represent Unit 42 by delivering expert-level presentations at key conferences, public speaking engagements, podcasts or webinars, and authoring influential thought leadership materials.

6. Peer Empowerment: Act as a resource for colleagues, sharing expertise and best practices to enhance team capabilities. Provide guidance to grow technical and strategic research acumen through personalized or group brown bag sessions.

7. Leverage AI for Analytic Workflows: Integrate Generative AI, NotebookLM, and other artificial intelligence and machine learning solutions across all phases of the intelligence lifecycle to improve analytic workflows. Use and develop new AI solutions to reduce research toil, query existing intelligence holdings, and accelerate report and presentation creation.

Your Experience

• 7 years minimum in the CTI field with experience in threat research, analytic production, and client-facing delivery.

• Strong knowledge of cyber threat actors, noteworthy attacks, and ability to quickly recognize inflection points, signalling shifts, evolution, or deviation from threat activity baselines or industry norms.

• Ability to contextualize cyber events, identify how the events fit into a current or historical pattern, the impact on an industry or organization, and tailored defensive recommendations.

• Experience operating under short fuse deadlines, managing concurrent tasks, and thriving in complex and sometimes ambiguous situations.

• Strong writing and presentation skills with the ability to communicate threat intelligence effectively to diverse audiences, including C-suite level customers.

• Deep experience with cyber threat intelligence frameworks and analytical techniques preferred.

• Demonstrated ability to coordinate with cross-organizational threat analysts, facilitating collaboration, and aligning efforts to achieve common goals.

• Experience presenting at CTI or cyber threat research conferences preferred.

• History of triaging and modeling open source data, telemetry, and other intelligence sources to quickly respond to requests for information. Preference for experience with Synapse or other hypergraphs.

• Experience with prompt engineering and leveraging Google’s AI capabilities to support development of intelligence products.

• Comfortable adapting to change as part of a growing team.

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 $162700 - $263150/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 Impact

• AI-Driven Detection & Automation: Lead end-to-end machine learning projects for threat detection. This encompasses defining the model architecture, sourcing and preparing data, building and managing training pipelines, deploying models into production, and monitoring their performance. Design, build, and deploy innovative security solutions leveraging Generative AI and agentic systems. Develop intelligent agents and workflows to automate threat hunting, accelerate malware analysis, and streamline threat intelligence processes.

• Research & Publication: Disseminate cutting-edge research findings and contribute to the security community by publishing results in technical blogs, industry white papers, and academic papers, particularly on topics related to malware analysis and AI for security.

• Collaboration & Communication: Work closely with cross-functional teams, including other security services: threat prevention, internet security and IoT security, endpoint security to integrate and deliver sustainable and quality coverage and defense.

Your Experience

• BS/MS/PhD degree in Computer Science, Cybersecurity, or a related field, or equivalent practical experience.

• 4+ years of experience in a research or engineering role, demonstrated experience in leading machine learning projects in malware domain or detection systems, including a strong understanding of model development, data preprocessing, and deployment.

• Proven experience in the complete software development lifecycle, with proficiency in one or more programming languages (e.g., Python, Go, C++).

• Strong experience in reverse engineering, system security, threat research, malware/code analysis or vulnerability research is a big plus

• A proven track of top tier publications in cybersecurity related areas is a big plus.

• Solid understanding of the threat landscape, including common attack vectors, malware techniques, and threat actor tactics is a plus.

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 $139,600 - $225,750/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

As a Security Researcher on this team, you will play a crucial role in developing automated defenses against emerging and sophisticated file-based threats and malware. Your expertise will be instrumental in translating deep threat knowledge into scalable, productized detection capabilities.

Your Impact

• Direct the in-depth analysis of emerging malware and sophisticated file-based threats from high-volume artifact data, maintaining an authoritative understanding of the threat landscape, actors, and attack vectors.

• Design and validate novel detection methods by leveraging data science techniques, including statistical modeling and machine learning, to automatically identify threats at scale.

• Translate research prototypes into robust, scalable, and extensible detection and prevention systems. Participate in the full software lifecycle, from architectural design through deployment.

• Serve as the critical link between research and engineering, transforming discoveries into impactful product features. Establish industry expertise through white papers and presentations.

Your Experience

• 3+ years of hands-on experience in malware analysis & detection (static and dynamic), threat research and reverse engineering on common file formats (PE, ELF, PDF, Office, Scripts, etc).

• Experience developing high-performance, scalable tools or systems for automated analysis and threat detection.

• Proficiency in at least one of the programming languages: Python, Golang, C.

• Creative thinker and team player. Have great passion and be highly self-motivated in data-driven security research.

• Excellent communication (written and verbal) and presentation skills;

• Experience with public cloud development, e.g., GCP, AWS, Azure is a plus

• Knowledge of AI/ML and experience in data driven approaches is a plus.

• Hands on and can-do attitude, willing to learn new technologies.

• Be comfortable working independently and efficiently.

• BS/MS in Computer Science or related fields with security research experience; PhD in cybersecurity is a plus.

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 $139600/YR - $225750/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.

• Currently enrolled in a Bachelor's or Master’s degree in Computer Science, Linguistics, Statistics, Biostatistics, Applied Mathematics, Operations Research, Economics, Natural Sciences, or related technical field.
  
• Experience in one area of computer science (e.g., Natural Language Understanding, Human Computer Interactions, Computer Vision, Machine Learning, Deep Learning, Algorithmic Foundations of Optimization, Quantum Information Science, Data Science, Software Engineering, or similar areas).
  

• Currently enrolled in a full-time degree program and returning to the program after completion of the internship.
  
• Currently attending a degree program in the United States.
  
• Experience as a researcher, including internships, full-time, or at a lab.
  
• Experience contributing research communities or efforts, including publishing papers in major conferences or journals.
  
• Experience with one or more general purpose programming languages (e.g., Python, Java, JavaScript, C/C++, etc.).
  

• Bachelor's degree or equivalent practical experience.
• 6 years of experience in product research in an applied research setting, or similar.
• Experience with qualitative research methods (e.g., interviews, ethnography, usability studies).
• Experience in programming languages used for data manipulation and computational statistics (e.g., Python, R, MATLAB, C++, Java, or Go).

• Master's degree or PhD in Human-Computer Interaction, Cognitive Science, Statistics, Psychology, Anthropology, or related field.
• Experience with quantitative methods and data analysis, including statistical analysis, modeling, and behavioral (logs) analysis.
• Experience using SQL or other data querying languages to analyze datasets and behavioral logs.
• Experience applying a variety of research methodologies (e.g., interviews, focus groups, field and lab studies, diary studies, and surveys) and an understanding of their strengths/limitations.
• Experience working in user trust, areas with high sensitivity or regulation, or an understanding of the regulatory landscape.