3 months ago
Bengaluru, IndiaSenior
Responsibilities
- Define the architecture and technology stack for an agent-native business applications platform supporting advertising revenue workflows.
- Build pipelines from business and customer signals through model inference, recommendation generation, output validation, and internal revenue-system integrations.
- Evaluate LLMs, multimodal systems, multi-agent orchestration frameworks, and recommendation, ranking, and forecasting models.
- Develop production-grade systems with error handling, explainability, auditability, and human-in-the-loop guardrails for pricing and financial decisions.
- Partner with ML, backend, frontend, data, and business teams to iterate on product capabilities.
- Drive technical decisions affecting revenue impact, product quality, scalability, and time to market.
Requirements
- Bachelor's degree in Computer Science or a related field.
- Experience building recommendation or decisioning systems, preferably in advertising, media, or revenue-platform environments.
- Strong understanding of modern LLMs and agentic systems, including latency, cost, and quality tradeoffs.
- Experience with LLM and multi-agent pipelines, prompting, tool use, orchestration, tradeoff analysis, and error handling.
- Production ML deployment experience, including model serving, containerization, CI/CD, and monitoring.
- Hands-on experience with PyTorch, Hugging Face Transformers, agent orchestration frameworks such as LangGraph, feature stores, and vector databases for RAG workflows.
- Experience evaluating recommendation and generative systems through human review, automated and offline metrics, and online A/B testing.
- Strong software engineering fundamentals and production experience with Java or Python.
- Ability to translate ambiguous business requirements into practical technical solutions and communicate tradeoffs clearly.
- Preferred: startup or founding-engineer experience or leadership of fast-moving GenAI or agentic product initiatives.
- Preferred: experience owning a business-facing or self-serve product from architecture through production deployment and operational support.
- Preferred: deeper experience in recommendation systems, pricing optimization, demand forecasting, uplift and churn modeling, or quoting and optimization.
- Preferred: experience improving inference cost and latency and building responsible AI guardrails for safety, compliance, auditability, and human review.
- Preferred: open-source contributions or publications in ML, recommender systems, or applied AI for revenue and decisioning.
Benefits
- Hybrid work approach with in-office work Monday through Thursday and flexible remote work on Fridays, subject to role and office policy.
- Benefits may include healthcare, life, accident, disability, commuter, retirement options, mental health and financial wellness support, and paid time off.
- Reasonable workplace accommodations are available in accordance with applicable law.
Categories
About Roku
Roku builds streaming players, Roku-branded TVs and audio gear, and the Roku OS licensed to TV manufacturers. Its platform supports ad-supported and subscription streaming, including The Roku Channel and Roku Originals, and underpins a significant advertising business. Founded in 2002 and headquartered in San Jose, it is a public company trading on NASDAQ under the ticker ROKU.