Lead and manage the design, development, and deployment of large language models (LLMs) across our privacy-first security platform. Responsible for driving end-to-end LLM research, engineering, and operational deployment, ensuring model performance, privacy compliance, and real-world security impact. This role combines technical leadership, hands-on engineering, and cross-functional collaboration to integrate LLMs into detection, classification, and response workflows.
Key Responsibilities
LLM Architecture & Model Development
Lead the research, design, and implementation of Transformer-based architectures (BERT, GPT, T5, LLaMA, etc.) optimized for security tasks.
Evaluate architectural designs for efficiency, robustness, privacy, and security.
Define threat-detection-specific requirements, including phishing, BEC, malware, and policy violation classification.
Optimize foundation model pre-training and distributed training strategies for compute efficiency.
Develop parameter-efficient fine-tuning strategies (LoRA, adapters, prefix tuning) for downstream security tasks.
Small Language Models & Edge Deployment
Build efficient Small Language Models (SLMs) for edge or customer environments with low latency (<100ms) and memory footprint (<2GB).
Implement model compression, quantization, pruning, and distillation techniques.
Ensure robust and secure deployment while maintaining high performance in constrained environments.
Data Strategy & Evaluation
Design and manage dataset pipelines, including privacy-preserving and synthetic data generation.
Define evaluation frameworks for adversarial robustness, false positive rates, bias, safety, and interpretability.
Monitor model performance and implement continuous improvement processes.
Cross-Functional Collaboration
Partner with Product and Security teams to translate business requirements into ML solutions.
Mentor teams and establish best practices for AI safety, privacy, and responsible ML development.
Align research outcomes with operational deployment and platform capabilities.
Core Technical Expertise
Transformer architectures and foundation models (BERT, GPT, T5, LLaMA)
Large-scale pre-training, distributed training, and compute optimization
Parameter-efficient fine-tuning (LoRA, adapters, prefix tuning, prompt tuning)
Model compression and efficiency techniques: quantization, pruning, distillation
Dataset engineering, synthetic data generation, and privacy-aware annotation
LLM evaluation: adversarial testing, bias assessment, robustness, and safety
Qualifications
Education & Experience
PhD in ML, NLP, CS, or equivalent industry experience (10+ years in ML/AI, with 5+ years focused on LLMs at scale)
Proven hands-on experience training, fine-tuning, and deploying LLMs in production with measurable impact
Experience in security, privacy, or safety-critical domains preferred
Preferred Certifications & Achievements
Publications in top-tier ML/NLP/security venues
Experience with edge/mobile deployment or embedded ML systems
Familiarity with RLHF, alignment, and responsible AI practices
Technical Skills
Proficient with PyTorch, distributed training frameworks (FSDP, DeepSpeed, Ray)
Strong understanding of privacy-preserving ML and security-focused AI applications
Experience with inference optimization frameworks (ONNX, TensorRT, vLLM, llama.cpp)
Scripting for automation and model deployment (Python, Bash, PowerShell)
Soft Skills
Excellent leadership and team management capabilities
Ability to make quick, high-impact decisions under pressure
Strong communication and presentation skills (technical & non-technical audiences)
Analytical thinking, creative problem-solving, and attention to detail
Customer-focused mindset and ability to work in fast-paced, high-stakes environments
Equal Opportunity Statement
We are committed to creating an inclusive workplace where everyone feels respected, valued, and supported.
We welcome applications from all qualified candidates regardless of age, gender, ethnicity, nationality, religion, disability, sexual orientation, or background. We believe diverse perspectives and experiences strengthen our team, foster innovation, and help us better serve our customers and communities.
If you require reasonable accommodation during the recruitment process, please let us know and we will do our best to support you.
