Applied Machine Learning Research Scientist Jobs

As a Research Scientist II on the Fraud Research team, you will help improve how Pindrop detects, scores, and investigates fraud and scams across voice and IVR interactions. You will work on applied machine learning problems that directly impact fraud and scam prevention for major enterprise customers, balancing core model development with real-world investigation and analysis. In this role, you will:

• Build and improve fraud risk models and scoring systems using a combination of audio, behavioral, and metadata-based signals.
• Analyze fraud patterns across customer environments and translate findings into measurable improvements in model performance, investigation workflows, or mitigation strategies.
• Research and build a scam detection stack, from conception to realization. 
• Partner with engineering and cross-functional teams to move successful research into production and improve fraud outcomes in live environments.
• Support high-priority fraud investigations by analyzing system behavior, fraudster attack patterns, and detection gaps, then recommending practical next steps for our customers.
• Improve the quality and precision of fraud-related identity signals, including voice-based indicators and repeat-offender detection.
• Design and maintain reproducible research workflows, internal tools, and evaluation pipelines that help the team experiment efficiently and measure impact clearly.
• Contribute to technical reviews, knowledge sharing, and research documentation that helps the broader organization understand and apply your work.
• Contribute to adjacent innovation areas, including emerging AI-assisted fraud-analysis workflows, when relevant to team priorities.

• You are persistent, curious, and scientifically rigorous, especially when working through ambiguous data, noisy signals, or fast-evolving fraud behavior.
• You are comfortable owning research workstreams from problem definition through experimentation, analysis, and recommendation.
• You communicate clearly with both technical and non-technical partners, and you can explain tradeoffs, assumptions, and results in a practical way.
• You care deeply about reproducibility, documentation, and building research that can stand up in real production settings.
• You are motivated by high-impact security and fraud problems and want your work to influence real customer outcomes.

Must-Haves:

• Advanced Degree (Master's or PhD) in Computer Science, Mathematics, Statistics, Engineering, Artificial Intelligence, or a related quantitative field, or equivalent applied research experience.
• Requires a minimum of 3 years of professional deep learning research experience explicitly focused on native video processing, computer vision, face recognition, generative AI, or deepfake detection.
• Strong Python skills and experience building research tooling, experimentation frameworks, or model evaluation workflows.
• Hands-on experience with modern machine learning frameworks such as PyTorch, TensorFlow, or Keras.
• A track record of translating research findings into practical improvements, whether in models, decision systems, or production-facing recommendations.
• Foundational knowledge of fraud, identity, consumer scams, authentication, risk scoring, or customer security concepts.

Nice-to-Haves:

• Experience working on fraud or scam detection in voice, IVR, contact center, authentication, or adjacent trust and safety environments.
• Experience working on building and/or fine-tuning multi-modal foundation models.
• Experience improving precision and recall in real-world detection systems, including thresholding, scoring, watchlists, or entity-resolution style signals.
• Familiarity with metadata-driven risk signals such as telephony, carrier, device, account, or behavioral indicators.
• Experience with sequence modeling, event-based risk modeling, or other approaches used to detect evolving attack behavior.
• Familiarity with LLM-enabled research workflows, retrieval systems, or observability tools used to support analyst or fraud-investigation productivity.
• Working knowledge of C/C++, Go, or other production-oriented languages.

This is a high-impact opportunity to join Pindrop's Research organization and work on fraud problems that matter in the real world. Your work will directly influence how we detect fraud, investigate suspicious behavior, and improve protection for major financial institutions and other enterprise customers.

You'll collaborate closely with strong technical peers across research and engineering, work on meaningful applied machine learning challenges, and help shape the next generation of fraud detection capabilities at Pindrop.

As a part of Pindrop, you'll have a direct impact on our growing list of products and the future of security in the voice-driven economy. We hire great people and take care of them. Here's a snapshot of the benefits we offer:

• Competitive compensation package, including RSUs (Restricted Stock Units) for all employees, so everyone shares in our long-term success.
• Remote-first environment - giving you flexibility and autonomy in how you structure your day.
• While we work flexibly, we prioritize meaningful in-person moments through regular team on-sites, company-wide events, and intentional gatherings that foster connection, collaboration, and shared success.
• Unlimited Paid Time Off (PTO)
• Generous health and welfare plans to choose from - including one employer-paid "employee-only" plan!
• Best-in-class Health Savings Account (HSA) employer contribution
• Low-cost vision and dental plans for you and your family, providing comprehensive coverage and peace of mind.
• Paid Parental Leave - Including birth, adoptive & foster parents
• One year of diaper delivery for your newest addition to the family! It's our way of welcoming new Pindroplets to the family!
• Recurring monthly phone and internet allowance to help cover essential connectivity costs and support flexible work.
• Enhanced fertility and GLP-1 benefits to support family-building journeys and personalized health needs.
• Annual Learning & Development stipend to support your professional growth, skill-building, certifications, and continued education.

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