# Staff Applied Scientist

**Company:** [Rokt](https://hotfix.jobs/companies/rokt)
**Location:** Austin, TX
**Role:** ML Engineering
**Salary:** $470k – $615k/yr
**Experience:** 10+ years
**Skills:** Machine Learning, Deep Learning, Transformers, graph neural networks, bayesian modelling, Reinforcement Learning, contextual bandits, representation learning, Embeddings, model optimisation, knowledge distillation, Python, PyTorch, TensorFlow
**Posted:** 2026-07-23

> 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.

## Job Description

## 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.).

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