Full-Time
Algo Developer
Hudson River Trading
501-1,000 employees
Proprietary algorithmic, high-frequency trading for institutions
Compensation Overview
$200k - $300k/yr
New York, NY, USA
In Person
Bachelor's
 Quantitative Finance (1) |
|---|
Get referred to Hudson River Trading
See people who can refer or advise you
- Brilliant analytical and problem solving skills.
- Ability to work creatively and independently on long-term technical problems.
- Familiarity with the C++ programming language.
- Possess a bachelor's degree in Mathematics, Computer Science, Statistics, Physics, or a related field.
- Capable of working independently as well as part of a team.
- Able to analyze and fix problems quickly.
- You learn quickly and apply new skills effectively.
- Build and maintain the models that drive trading.
- Apply rigorous statistical analysis to vast quantities of market and financial data to produce predictive trading models.
- Run models live on high-performance trading infrastructure.
- Analyze daily performance of models to maintain ongoing profitability.
- Collaborate with fellow algo developers and core developers to research, develop, and test novel order execution and model training methods to increase trading efficiency.
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
Get referred to Hudson River Trading
See people who can refer or advise you
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.
Help us improve and share your feedback! Did you find this helpful?
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
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.
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.
Gray Swan, an AI security company born from Carnegie Mellon University research, has raised $40 million in a Series A round co-led by Wing Venture Capital and Madrona. Obvious Ventures, Snowflake Ventures, Hudson River Trading, Samsung Next and Magarac Venture Partners also participated. The company, founded by Matt Fredrikson and Zico Kolter, provides security platforms for AI models and agents. Gray Swan is cited in 11 recent frontier model system cards from Anthropic, OpenAI and Meta, and its benchmarks are embedded in safety evaluation processes for advanced AI models. The platform includes three components: Cygnal for real-time AI protection, Shade for automated adversarial testing, and Arena, a global red-teaming network with over 15,000 researchers. Gray Swan works with over 20 customers and has partnered with Snowflake to integrate its security capabilities.