data Science Engineering Manager

We are hiring an Engineering Manager to own and grow the data Science group - the R&D team behind security and safety AI models and the data platform that powers them. You will lead a multidisciplinary team of ML engineers, data scientists, and software engineers who ship Real-Time inference at scale, automated red-teaming of GenAI systems, and the Databricks/Spark data platform underneath. This is a hands-on people-leadership role: you set technical direction, are accountable for delivery and quality, and you build and grow the team.

What your team owns The group is responsible for a large Python Rust PySpark monorepo (dozens of production services and shared libraries) spanning three connected domains: 1. Content-moderation inference at scale Real-Time, multi-tenant detection across text, image, video, and audio - hate speech, CSAM, nudity, child grooming, extremism, PII, prompt injection, age estimation, and more - served through an in-house ActiveServe framework over NVIDIA Triton and a Rust detection monolith, on latency-sensitive, SLA-bound, customer-facing traffic with per-customer custom models.

• GenAI safety & red-teaming Automated red-teaming that attacks customers' LLM applications with a research-driven attack taxonomy and measures attack-success rate, alongside the defensive side - LLM-as-judge escalation to cut false positives and the tooling that authors and refines moderation policies - built on a multi-provider LLM foundation (Bedrock, Anthropic, OpenAI, Gemini, xAI Grok) and forming leading edge into agentic-AI safety. 3. data platform & MLOps An end-to-end lakehouse and MLOps stack on Databricks - bronze/silver/gold ingestion, PySpark pipelines, and model training, versioning, and promotion through MLflow / Unity Catalog into Triton serving - with the performance-critical hot paths engineered in Rust (PyO3/maturin) for sub-millisecond, high-QPS matching and detection. What you'll do* Lead and grow the team - mentor ML engineers, data scientists, and software engineers, and own hiring, onboarding, 1:1s, career development, and performance.

Set direction and deliver - set technical direction and standards, turn company and product goals into a prioritized roadmap, and own the quality, reliability, and delivery of the systems above across parallel workstreams.

Champion excellence and partnership - stay hands-on to review designs and unblock the team, drive engineering excellence (testing, observability, CI/CD, on-call, cost/latency), keep the team at the state of the art in ML, LLMs, and GenAI safety, and partner with Product, Platform, and GenAI-safety stakeholders. Leadership competencies* People-first: builds trust, grows engineers, and creates a healthy, inclusive, high-ownership culture.

Outcome-oriented: drives clarity, sets priorities, and delivers under ambiguity without micromanaging.

Technical credibility: earns the team's respect through sound judgment on architecture and trade-offs.

Systems thinker: balances short-term delivery against long-term platform health, cost, and tech debt. the GenAI safety and security platform that keeps online experiences safe. We provide AI-driven detection, moderation, and red-teaming that protect billions of users across social platforms, marketplaces, gaming, and - increasingly - the GenAI applications reshaping the internet. Our data Science group builds the machine-learning and data systems at the core of that mission.Requirements: What we're looking for (must-have) Leadership & communication - a proven people manager of engineering or data -science teams (or a strong tech lead ready to step into formal management), with excellent communication and stakeholder management.

• Hands-on engineering and ML at scale - strong production Python and software-engineering background with solid ML / data -science foundations (training, evaluation, deploymentThis position is open to all candidates.