Sr. Sw Engineer, Machine Learning Job at Roku (Bengaluru)

Job Description

We are hiring a Senior Engineer to lead the architecture and implementation of a next-generation, agent-native, AI-powered business applications platform. This is a high-impact role focused on building intelligent, recommendation-driven experiences that make day-to-day revenue decisions with pricing, booking, upsells, retention, and media planning faster, smarter, and more accessible to the teams that run Roku's advertising business. You will architect and build the end-to-end system for AI-driven recommendations and decisioning, from business and customer signals through to actionable, validated outputs. You will work closely with ML, backend, frontend, data, and business stakeholders to deliver a production-ready platform that improves speed, accuracy, and scalability across the advertising revenue workflow.

Job Responsibility

Define the technical architecture and overall stack for an agent-native business applications platform spanning pricing guidance, booking and order intelligence, upsell recommendations, churn and retention prediction, media planning, deal scoring, revenue forecasting, and more
Evaluate LLMs, multimodal systems, multi-agent orchestration frameworks, and recommendation, ranking, and forecasting models for product use
Design and build the pipeline from business and customer signals to model inference, recommendation generation, output validation, and integration with internal revenue systems and APIs
Build production-grade systems with strong error handling, output validation, explainability, auditability, and human-in-the-loop guardrails for high-stakes pricing and financial decisions
Partner cross-functionally with ML, backend, frontend, data, and business teams to iterate quickly based on feedback and business needs
Drive technical decisions that directly influence 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, ideally in advertising, media, or revenue-platform environments
Strong understanding of modern LLMs and agentic systems, and the ability to evaluate latency, cost, and quality tradeoffs
Solid experience with LLM and multi-agent pipelines, including prompting, tool use, orchestration, tradeoff analysis, and error handling
Experience deploying ML systems in production, including model serving, containerization, CI/CD, and monitoring
Hands-on experience with modern ML frameworks and tooling such as PyTorch, Hugging Face Transformers, agent orchestration frameworks (e.g., LangGraph or similar), feature stores, and vector databases for RAG workflows
Experience designing evaluation approaches for recommendation and generative systems using human review, automated and offline metrics, and online A/B testing
Strong software engineering fundamentals and solid production experience in Java or Python
Ability to translate ambiguous business requirements into practical technical solutions and communicate tradeoffs clearly to cross-functional partners

Nice to have

Startup or founding-engineer experience, or experience leading fast-moving Gen AI or agentic product initiatives
Experience owning a business-facing or self-serve product from architecture through production deployment and operational support
Deeper background in recommendation systems, pricing optimization, demand forecasting, uplift and churn modelling, or quoting and optimization
Experience improving inference cost and latency, and building responsible AI guardrails such as safety, compliance, auditability, and human review mechanisms
Open-source contributions or publications in ML, recommender systems, or applied AI for revenue and decisioning

What we offer

Global access to mental health and financial wellness support and resources
Healthcare (medical, dental, and vision)
Life, accident, disability, commuter, and retirement options (401(k)/pension)
Time off in accordance with local leave policies

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Sr. Sw Engineer, Machine Learning

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