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RoktRoktAustin, TX

Staff Applied Scientist

Lead applied ML research, experimentation, and production model development to optimize auctions and decisioning in Rokt's multi-sided ecommerce marketplace, powering billions of transactions. Requires PhD (or equiv), 10+ years building production ML systems, and deep expertise in at least two advanced ML areas such as deep learning architectures, RL, or revenue optimization.

470k – 615k/yr
Hybrid10+ YOEML Engineering

About the role

Responsibilities

Technical

  • Own the research, design, development, testing, deployment and maintenance of machine learning systems and services at Rokt.
  • Optimise auction and decisioning logic, applying model predictions to maximise value across Rokt’s multi-sided marketplace.
  • Conduct applied ML research, prototype new modeling approaches, and rigorously test innovations.
  • Evaluate and improve model performance, ensuring robustness, scalability, and interpretability.
  • Translate complex business needs into practical ML solutions, collaborating with product and engineering teams.
  • Stay ahead of emerging ML trends, contributing to knowledge sharing through tech talks, brown bags, and best practice evangelism.

Leadership

  • Act as technical and project leader of a small team of specialists.
  • Provide leadership on complex technical issues.
  • Set standards for technical excellence - from coding to architectural best practices.
  • Work cross-functionally with engineering and product leadership to plan and manage delivery expectations of roadmap items.
  • Actively monitor progress and intervene where required to mitigate risks and bottlenecks, managing expectations within and outside the team.

Requirements

  • PhD or equivalent experience in Computer Science, Statistics, Mathematics, or related field with specialization in ML, AI, or Information Retrieval, and experience leading PhD level scientists/engineers on projects.
  • 10+ years of industry experience building production-grade ML systems.
  • Deep expertise in at least two of the following:
    • ML for Ads, E-commerce, or Two-Sided Marketplaces
    • Deep Learning Architectures e.g MMoE, PLE, DCN, Transformers, Graph Neural Networks
    • Bayesian Modelling & Probabilistic Methods
    • Reinforcement Learning (Contextual Bandits, Policy Optimization)
    • Price & Revenue Optimisation
    • Representation Learning & Embeddings
    • Model Optimisation (quantisation, distributed training, GPU optimisation, JIT compilation, mixed precision, inference optimisation)
    • Knowledge Distillation

Nice-to-Haves

  • Pathways to Principal Applied Scientist (IC Track) and Applied Science Manager/Director (People Leader track) per your preferences and abilities.

Compensation

  • Target total compensation ranges from $470k - $615k, comprised of a fixed annual salary of $290k - $360k, plus employee equity plan grant.
  • Equity in a profitable, fast-growing company approaching $1 Billion in revenue.
  • Dollar-for-dollar 401K matching plan (up to 4% of fixed annual remuneration).
  • Fully funded health insurance (Dental, Optical, and Medical).
  • Generous allowances for wellness, technology, mobile, and transit.
  • Daily catered lunch, stocked pantry & fridges.
  • Extra leave (bonus annual leave, sabbatical leave etc.).

Skills

Machine LearningDeep LearningTransformersgraph neural networksbayesian modellingReinforcement Learningcontextual banditsrepresentation learningEmbeddingsmodel optimisationknowledge distillationPythonPyTorchTensorFlow

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