Teams at LVT

Lead end-to-end ML data engineering: build and own pipelines that convert raw telemetry and video into versioned, governed training and benchmark datasets. Design schema, storage, dataset versioning, governance, reader/writer libraries, and integrations for researchers; partner with annotation, edge, and MLOps teams and provide technical mentorship.

Lead end-to-end model lifecycle as infrastructure: standardized packaging, model CI/CD, serving with versioned contracts, automated deployment/rollback, monitoring and drift detection. Extend platform discipline to LLM/VLM/agentic workloads (prompt/versioning, generative evaluation, guardrails, token cost/latency observability). Define API boundaries, enable self-serve safe deployments, own operational seams (vector stores, tracing), and mentor engineers to grow the ML/LLM ops function.

Own end-to-end delivery of a GenAI-powered security deterrence product: design services and APIs, integrate detection models with prompting and voice/TTS, build evaluation and regression suites, ensure precision and safety for real-world actuations, and drive build-vs-buy decisions while collaborating across platform, data, and ML teams.