Senior Machine Learning Engineer

About the Role

The NOVA AI team builds the platform and AI that powers world-class support across mobile, web, and voice at global scale. We are now hiring a Senior ML Engineer to build and scale an autonomous support agent that resolves customer issues end-to-end. You'll push the state of the art in GenAI for customer service-LLM orchestration, evaluation, safety guardrails, multilingual support-while holding a very high bar for reliability and cost efficiency. We are still at an early stage and value candidates with bias for action who get creative with GenAI tools to accelerate execution and experimentation.

What the Candidate Will Need / Bonus Points

---- What the Candidate Will Do ----

1. Work on agent architecture: agentic planning and execution loops, long-term memory, persona/voice, knowledge routing, and policy enforcement for compliant, on-brand conversations.
2. Ship production systems that handle millions of conversations with rigorous SLOs, fallbacks, and canaries; design graceful degradation (e.g., human handoff) and safety guardrails (prompt-injection, jailbreak, PII redaction).
3. Advance retrieval & reasoning: Build next-generation retrieval and reasoning pipelines, where the agent can search across different knowledge sources, apply policy-driven tools, and call structured workflows and ensure that responses are consistently grounded.
4. Establish evals that matter: offline rubrics, simulated scenarios, safety tests, cost/latency tradeoff suites, and LLM-as-judge (with calibrated human review) wired into CI/CD and experiment platforms.
5. Drive automation at scale: partner with Product/Design/Operations on coverage, policy alignment, localization, and rollout strategy to better customer experience and reduce cost per contact.

1. Background in LLM-driven systems (inference optimization, prompt/program design, fine-tuning, distillation/LoRA, safety/guardrails, evals).
2. Strong software engineering in Python
3. Track record of shipping customer-facing intelligent experiences with measurable impact (A/B testing, metrics literacy).
4. Bachelor's degree (or above) in Computer Science or related field

1. Agentic architectures in production (planner/executor, memory, multi-step reasoning) and RAG over complex, policy-heavy knowledge bases.
2. Experience building support automation for large consumer platforms (routing, policy codification, internal tooling, co-pilot/auto-resolve).
3. Multilingual NLU/NLG (code-switching, low-resource languages), hallucination mitigation, safety red-teaming, and privacy-by-design.
4. Practical expertise balancing speed and reliability at scale: experiment frameworks, feature flags, canary/guarded rollouts, and clear kill-switches.