Job description

Optiver is a seeking a Machine Learning Performance Engineer to join our team, focusing on a pivotal AI initiative. This role would offer the opportunity to have significant impact across Machine Learning infrastructure, training, and inference challenges to advance our futures trading strategies. What you'll do As a Machine Learning Performance Engineer, your key responsibilities include: Building scalable and robust training and inference pipelines for deep learning Diving into internals of open-source deep learning frameworks and enhance their functionality Identifying and eliminate performance bottlenecks Collaborating closely with researchers and other engineers Developing an in-depth understanding of trading systems What you’ll get You’ll join a culture of collaboration and excellence, surrounded by curious thinkers and creative problem-solvers. Motivated by a passion for continuous improvement, you’ll thrive in a supportive, high-performing environment alongside talented colleagues, collectively tackling some of the toughest challenges in the financial markets. In addition, you’ll receive: The opportunity to work alongside best-in-class professionals from over 40 different countries A highly competitive compensation package Global profit-sharing pool and performance-based bonus structure 401(k) match up to 50% Comprehensive health, mental, dental, vision, disability, and life coverage 25 paid vacation days alongside market holidays Extensive office perks, including breakfast, lunch and snacks, regular social events, clubs, sporting leagues and more Who you are Strong knowledge of low-level GPU programming with CUDA, including Tensor Cores, cooperative groups, graphs, and warp-level intrinsics Expertise in internals of deep-learning frameworks like PyTorch, JAX, TensorFlow, etc. Deep understanding of computer architecture Experience in C++ and Python Nice to have Experience with JAX ecosystem (XLA, Flax, etc.) Familiarity with GPU libraries and tools such as Triton, CUB, cuDNN, and cuBLAS Linux system programming experience Experience with large-scale distributed training Contributions to open-source projects related to data science and machine learning Who we are At Optiver, our mission is to improve the market by injecting liquidity, providing accurate pricing, increasing transparency and stabilizing the market no matter the conditions. With a focus on continuous improvement, we prioritize safeguarding the health and efficiency of the markets for all participants. As one of the largest market making institutions, we are a respected partner on 100+ exchanges across the globe. Our differences are our edge. Optiver does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, physical or mental disability, or other legally protected characteristics. Below is the expected base salary for this position. This position will also be eligible for a discretionary bonus and Optiver’s benefits package with the benefits listed above. Base Salary Range $200,000 — $200,000 USD

Requirements

Must-haves

As a Machine Learning Performance Engineer, your key responsibilities include:
Building scalable and robust training and inference pipelines for deep learning
Diving into internals of open-source deep learning frameworks and enhance their functionality
Identifying and eliminate performance bottlenecks
Collaborating closely with researchers and other engineers
Developing an in-depth understanding of trading systems
What you’ll get
The opportunity to work alongside best-in-class professionals from over 40 different countries
A highly competitive compensation package
25 paid vacation days alongside market holidays
Extensive office perks, including breakfast, lunch and snacks, regular social events, clubs, sporting leagues and more
Strong knowledge of low-level GPU programming with CUDA, including Tensor Cores, cooperative groups, graphs, and warp-level intrinsics
Expertise in internals of deep-learning frameworks like PyTorch, JAX, TensorFlow, etc.
Deep understanding of computer architecture
Experience in C++ and Python

Nice-to-haves

Global profit-sharing pool and performance-based bonus structure
Experience with JAX ecosystem (XLA, Flax, etc.)
Familiarity with GPU libraries and tools such as Triton, CUB, cuDNN, and cuBLAS
Linux system programming experience
Experience with large-scale distributed training
Contributions to open-source projects related to data science and machine learning

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningaipython

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)