Level

Virtu

Machine Learning Researcher

AI in this role

pytorchtensorflowjax

Virtu is a quantitative trading firm that uses cutting-edge models and infrastructure to provide liquidity to the global markets.

As a Machine Learning Researcher at Virtu, you'll pursue high-impact research opportunities within a results-oriented, agile organization. This role offers the rare combination of intellectual challenge and direct business impact. You'll tackle complex problems without obvious solutions, taking ownership of our entire modeling ecosystem—from feature engineering and deep learning architecture design to training dynamics and execution strategy. Your innovations will directly influence how we operate in markets globally, making a tangible difference in a field that demands constant evolution, creative problem-solving, and first-principles thinking.

A sense of curiosity, strong technical skillset, and collaborative mentality make you a good fit for this position, regardless of what industry you come from. 

The Role

  • Investigate, evaluate, and prototype innovative algorithmic solutions using novel machine learning and deep learning techniques. Reinforcement learning experience is a bonus
  • Results oriented mindset with a focus on developing deep learning models that directly impact P&L
  • Implement sophisticated ML approaches for forecasting, feature engineering, and optimization challenges
  • Conduct empirical ML research across multiple problem domains, rapidly prototyping and iterating novel architectures in Python/PyTorch/TensorFlow to solve challenging market problems
  • Apply logical and mathematical reasoning to translate cutting-edge research methods between application areas. Adapt techniques from your area of expertise to achieve breakthrough results in the financial markets
  • Partner with quantitative traders, researchers, and developers across teams to transform market insights into actionable data features and predictive models

 

The Candidate

  • Minimum 2 years of applied experience developing deep learning solutions across diverse fields
  • Proven capability in applying machine learning methodologies between different problem domains and application areas
  • Strong production mindset with emphasis on delivering solutions that create bottom-line value and tangible business outcomes
  • Proficient in rapid prototyping and iterative development using Python and contemporary deep learning frameworks
  • Advanced programming expertise in areas such as core PyTorch/JAX framework development. Exposure to C++ in production environments is a plus
  • Comfortable partnering with other researchers, developers, and traders and working on cross-functional projects in a collaborative environment

 

Salary Range: $200,000 - $300,000 (salary range is exclusive of bonuses, benefits or other categories of compensation)

Virtu Financial is an equal opportunity employer, committed to a diverse and inclusive workplace, welcoming you for who you are and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

How we rate this

Machine Learning Researcher at Virtu rates 94 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

PyTorchTensorFlowJax

Questions you could be asked

  1. What's a project where you used PyTorch hands-on?
  2. Walk me through how you've used TensorFlow in your day-to-day work.
  3. What are the limits of Jax that you've run into, and how did you work around them?
  4. How would you decide a model or AI system is ready to ship?
  5. Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

  • List these exact terms on your resume: PyTorch, TensorFlow, and Jax. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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