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Urgent! Machine Learning Research Engineer Job Opening In New York – Now Hiring Optiver

Machine Learning Research Engineer



Job description

Optiver is a seeking a Machine Learning Research 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:

  • Conduct innovative research on deep learning for price forecasting 

  • Build scalable and robust training and inference pipelines for deep learning

  • Dive into internals of open-source deep learning frameworks and enhance their functionality

  • Collaborate closely with researchers and other engineers

  • Develop 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: 

  • PhD or equivalent industry experience in a field related to machine learning

  • Expertise in building deep-learning models in PyTorch, JAX, or TensorFlow

  • Experience in programming in Python

  • Experience in computationally intensive research on very large data sets
  • Nice to have:

  • Experience with JAX ecosystem (XLA, Flax, etc.)

  • Experience in programming for GPUs or other accelerators (CUDA, Triton, Pallas, etc.)

  • Contributions to open-source projects related to data science and machine learning

  • Strong publication record at conferences like NeurIPS, ICML, etc.

  • Expertise in internals of deep-learning frameworks like PyTorch, JAX, TensorFlow, etc.

  • Experience with large-scale distributed training

  • Experience in programming in C++
  • Who we are:


    Optiver is a tech-driven trading firm and leading global market maker.

    As one of the oldest market making institutions, we are a trusted partner of 70+ exchanges across the globe.

    Our mission is to constantly improve the market by injecting liquidity, providing accurate pricing, increasing transparency and acting as a stabilizing force no matter the market conditions.

    With a focus on continuous improvement, we participate in the safeguarding of healthy and efficient markets for everyone who participates.


    Diversity statement


    Optiver is committed to .

    Below is the expected base salary for this position.

    This is a good-faith estimate of the base pay scale for this position and offers will ultimately be determined based on experience, education, skill set, and performance in the interview process.

    This position will also be eligible for a discretionary bonus (if determined by Optiver) and Optiver’s benefits package with the benefits listed above.

    Base Salary Range
    $200,000—$200,000 USD You are viewing: Machine Learning Research Engineer


    Required Skill Profession

    Computer Occupations



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      Unlock Your Machine Learning Potential: Insight & Career Growth Guide


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    • Interview Tips for Machine Learning Research Engineer Job Success
      Optiver interview tips for Machine Learning Research Engineer

      Here are some tips to help you prepare for and ace your job interview:

      Before the Interview:
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      • Practice: Prepare answers to common interview questions and rehearse using the STAR method (Situation, Task, Action, Result) to showcase your skills and experiences.
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