Senior Software Engineer - Machine Learning

Responsibilities:
Apply state-of-the-art ML to search using techniques in deep learning, bandits, transformers, LLMs, causal inference, and optimisations to make our users more delighted and engaged on the platform.
Run online A/B tests and analyse them against the critical business KPIs.
Collaborate with US engineering teams as well as cross-functional teams to translate business requirements into technical specifications.
Nurture our ML ecosystem to make it withstand scale, developer velocity, and future business shifts.
Provide technical leadership to drive the technical and ML roadmap for search ranking and monetisation.
Help recruit new engineers, interview, train, and mentor new team members.
Requirements:
6+ years of experience (or PhD with 5 years of experience) applying Machine Learning to concrete problems at large-scale in domains like recommendation, search, or ads.
Strong computer science fundamentals with the ability to convert ideas to code with ease.
Good understanding of machine learning fundamentals like classification, deep neural nets, and sequence-based models; familiarity with modern NLP stack and multi-modal representation learning is a plus.
Experience working with big data systems (Spark, S3 and Airflow) and proficiency in Java, Scala, or Python.
Good understanding of system architecture.
Experience in big data technologies and streaming architecture, data pipelines, etc.
Master's degree in Computer Science, Statistics, or related field; PhD in Computer Science or related fields preferred.
You have built fluency across the agentic engineering toolchain, coding harnesses like Claude Code or Cursor, MCP servers, custom skills, or agent frameworks. And you can describe projects where you shipped real work with these tools.
You know how to drive an agent, verify its output, and ramp up on an unfamiliar codebase with an agent you built.

Experience
6-10 yrs