Hudson River Trading
Proprietary algorithmic, high-frequency trading for institutions
Algorithm Developer – 2024 Grads
This job posting does not specify a particular location or travel requirements. The company mentions having offices all over the globe, so potential candidates should be open to working in various locations and collaborating with a diverse staff.
About the job
- You are a full-time undergraduate, masters, or PhD student in a quantitative discipline (math, physics, computer science, statistics, or a related program) who is eligible for full-time roles in 2024
- Experience programming in Python and/or C++
- Experience with statistical analysis, numerical programming, or machine learning in Python, Pandas/Numpy, R, and/or MATLAB
- A passion for applying quantitative models and technology toward solving real-world problems
- Brilliant analytical and problem-solving skills
- Ability to work creatively and independently on long-term technical problems
- You are capable of working independently as well as part of a team
- You can analyze and fix problems efficiently
- You learn quickly and apply new skills effectively
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
PicoJool, a startup backed by former Intel chief executive Pat Gelsinger, has raised $27.5 million in Series A funding to address bandwidth challenges in AI data centres. Socratic Partners led the round, with participation from Hudson River Trading, bringing total funding to $39.5 million. The company develops optical chips based on Vertical Cavity Surface Emitting Laser technology, which transmits data through light signals rather than traditional copper wires. This enables faster, more energy-efficient communication between AI processors in large clusters. PicoJool offers high-speed 100G and 200G VCSEL products, with its MicroVCSEL platform providing up to 3.2 terabits per second of bandwidth. The funding will support commercialisation efforts, including mass production preparation with WIN Semiconductors and expansion of US and Taiwan teams. Gelsinger noted that connectivity has become a defining constraint on AI performance globally.
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.
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.
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.
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.