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Hudson River Trading

Hudson River Trading

Proprietary algorithmic, high-frequency trading for institutions

Algorithm Developer Intern - Quantitative Research & Trading, Summer 2027

Summer 2027
$108.75 - $191.25/hr

+ Signing bonus + Company-paid housing + Meals

Internship
PhD
London, UK+1 more

More locations: New York, NY, USA

Remote

About the job

Requirements
  • You must be a full-time PhD student in a quantitative discipline such as mathematics, physics, computer science, statistics, operations research, or machine learning.
  • Fluency in Python is required.
  • You must have experience with statistical analysis, numerical programming, or machine learning using Python, Pandas, NumPy, R, and/or MATLAB.
  • You must have strong communication skills.
Responsibilities
  • Apply advanced research experience and expertise to academic research and real-world trading problems across time horizons and machine learning strategies.
  • Use proprietary Python and C++ infrastructure together with third-party tools to conduct quantitative research and data analysis.
  • Use machine learning and time series techniques to derive insights into market behavior from large and complex datasets.
  • Use the compute cluster to run simulations and process data.
  • Build predictive models for financial markets using market and non-market data.
  • Attend and participate in technology talks covering markets and the company’s trading philosophy.
  • Participate in the summer curriculum of speakers, trading games, mentorships, and social events.
Desired Qualifications
  • Apply research expertise to identify new opportunities in worldwide markets.

About the company

What Hudson River Trading does: It uses computer-based trading to buy and sell financial instruments for institutional clients, using its own private algorithms and fast computers to trade in global markets. How its products work: The firm designs mathematical models and software that scan market data and place many trades in milliseconds. It aims to earn small profits on a huge number of trades by moving quickly and reacting to price changes across asset classes worldwide. How it differs from competitors: HRT relies on in-depth research and proprietary algorithms, large-scale computing, and a global network of offices to trade across many markets. This combination helps it stay competitive against other high-frequency trading firms and banks. What its goal is: To generate reliable revenue by executing a high volume of fast trades while continually improving its models and technology through ongoing research and development.

Company Size

501-1,000

Company Stage

Debt Financing

Total Funding

$630M

Headquarters

New York City, New York

Founded

2002

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Simplify's Take

What believers are saying

  • Q2 2026 trading revenue hit $11.4 billion, signaling extraordinary monetization.
  • HRT opened 2026 roles for AI researchers and low-level engineers in London and New York.
  • May 20, 2026 Lambda contract secured 1,000-plus Nvidia Blackwell systems for HRT.

What critics are saying

  • Jane Street's April 24, 2026 $40 billion haul shows HRT faces a brutal arms race.
  • SEC comment activity on August 17, 2026 signals regulatory scrutiny around locked and crossed markets.
  • Heavy reliance on expensive AI compute turns one technology reset into an existential margin collapse.

What makes Hudson River Trading unique

  • HRT blends market-making, proprietary AI labs, and custom GPU clusters across assets.
  • August 20, 2026 CoreWeave deal scaled HRT's AI research infrastructure for trading models.
  • HRT provides liquidity directly to clients worldwide, unlike pure prop rivals.

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Benefits

Dental, Vision, Disability, Health, Life, and Supplemental Life Insurance

Flexible Spending Account

Health Savings Account

401(k)

Paid Time Off

Free lunch or snacks

Gym membership

Company News

Yahoo Finance
Sep 15th, 2026
Polaris Electro-Optics raises $50M Series B to scale FenGlass modulator platform for AI infrastructure

Polaris Electro-Optics has raised $50 million in Series B funding led by Walden Catalyst Ventures to commercialise its FenGlass electro-optic modulator platform for AI infrastructure. New investors include Socratic Partners, Cambium Capital, Knollwood, and Hudson River Trading, alongside existing backers Koch Disruptive Technologies, M Ventures, and others. The California-based startup addresses data movement bottlenecks in AI workloads by enabling 400 Gbps per lane optical interconnects. Its proprietary ferroelectric nematic glass integrates directly onto silicon photonic wafers using standard manufacturing processes, eliminating trade-offs between manufacturability, reliability, and bandwidth. Polaris has completed critical reliability tests and validated compatibility with industry packaging standards. The company targets its first product launch for 2027, partnering with optical module makers and cloud infrastructure providers. Founded in 2021 as a University of Colorado Boulder spinout, Polaris operates facilities in Carlsbad and Boulder.

PR Newswire
Sep 10th, 2026
Positron AI raises $875M at $5B valuation for next-gen inference chips

Positron AI has raised $875 million at a $5 billion valuation to fund its next-generation AI inference hardware. The Series C round was co-led by NEA, Atreides Management, Valor Equity Partners, Andra Capital, SemiAnalysis Capital, and Silicon Graphics founder Jim Clark. The company builds memory-first inference systems designed to run AI models more efficiently than traditional approaches. Positron is deploying over 50 racks of its first-generation Atlas system at Oracle Cloud Infrastructure, with customers including Jump Trading and i3d.net. The funding will support the tapeout of Asimov, Positron's next chip on TSMC's N3P process, scheduled for late 2026 with production in second-half 2027. It will also fund production of Titan, its next-generation system combining multiple Asimov chips. The architecture uses commodity LPDDR5X memory rather than constrained HBM supply chains.

Logos Press
Sep 6th, 2026
25-year-old British entrepreneur becomes Europe's youngest self-made billionaire with $3B AI chip startup

James Dacombe, a 25-year-old British entrepreneur, has become Europe's youngest self-made billionaire after his AI chip company Olix raised funding at a valuation exceeding $3 billion. This nearly tripled the company's $1 billion valuation from February, when it secured $220 million. Dacombe, who began programming at 13 without formal training, left school as a teenager with support from the Thiel Fellowship. He founded CoMind in 2017-2018, developing non-invasive brain monitoring technology. The startup raised $60 million in 2025, bringing total funding to $102.5 million. Launched in 2024, Olix develops specialised chips for AI inference. Investors include Arm, Netflix co-founder Reed Hastings, and the British Sovereign AI Fund. Commercial chip shipments are expected by late 2027.

Gimlet Labs
Sep 4th, 2026
Announcing Gimlet's Series B

Today, we are announcing our $300M Series B raise, led by Andreessen Horowitz and joined by Sapphire Ventures, Menlo Ventures, 645 Ventures, Arm, Eclipse, Emergence, Factory, Hudson River Trading, M12, OnePrime Capital, Prosperity7, QuantumLight, Samsung Ventures, Tiger Global Management, Triatomic, Wing Ventures, and XTX Markets.

Traders Union
Aug 3rd, 2026
Olix raises $312M at $3.3B valuation to challenge Nvidia with photonic AI chips

London-based AI chip developer Olix has raised $312 million in a funding round led by New York investment firm Fundomo, with participation from Arm, Hudson River Trading, and Netflix co-founder Reed Hastings. The round values the company at $3.3 billion, up from just over $1 billion in February. Founded in 2024 by James Dacombe, Olix plans to tape out its chips later this year and deliver first products to customers in 2025. The company employs over 140 staff across London, Bristol, Toronto, and Austin. Olix differentiates itself with a photonic interconnect that uses lasers to move data between chip clusters with greater energy efficiency. The company also avoids scarce semiconductor components and uses proprietary AI tools to accelerate development, including work on its compiler. Matt Briers, former CFO at fintech Wise, joins as chief financial officer.