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Home Based High Frequency Trading Software Engineer Jobs

We are seeking a Machine Learning Engineer to join the High Frequency Trading Technology team. This ... Experience with machine learning software libraries such as TensorFlow or PyTorch * Experience ...

Hardware Machine Learning Engineer

Chicago, IL · On-site

$127K - $167K/yr

We build the hardware, the software, and the infrastructure, so when you hit a bottleneck, you can ... Background in latency-sensitive or resource-constrained systems including high-frequency trading ...

... scale and high-frequency market data. * Collaborate with developers, traders, and fellow ... ML-based approaches, and understanding of overfitting risk. * Deep interest in market dynamics ...

C++ Developer

Chicago, IL · On-site

$90K - $150K/yr

... high-frequency trading. * Develop Risk Management and Compliance Tools: Create tools for risk ... Practical, hands-on experience in software development is valued. A formal degree is not a strict ...

NOTE: this role can be anywhere in the United States as the position is not office-based. With over ... like high-frequency trading, simulation, real time data processing etc. are also okay. * You ...

Senior Software Engineer

Chicago, IL

$126K - $166K/yr

... trade a diverse set of instruments across a wide range of financial marketplaces ... This smaller, focused team comes with a high degree of responsibility and ownership. Our systems ...

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Home Based High Frequency Trading Software Engineer information

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$63.5K

$147.5K

$205.5K

How much do home based high frequency trading software engineer jobs pay per year?

As of Jun 12, 2026, the average yearly pay for home based high frequency trading software engineer in the United States is $147,524.00, according to ZipRecruiter salary data. Most workers in this role earn between $120,000.00 and $173,000.00 per year, depending on experience, location, and employer.

What is the difference between Home Based High Frequency Trading Software Engineer vs Home Based Quantitative Analyst?

AspectHome Based High Frequency Trading Software EngineerHome Based Quantitative Analyst
Required CredentialsComputer Science degree, programming skills, knowledge of trading algorithmsMathematics, statistics, finance degrees, programming skills
Work EnvironmentDeveloping and optimizing trading algorithms, coding in C++, PythonData analysis, modeling, research, often using statistical software
Employer & Industry UsageTrading firms, hedge funds, financial institutionsHedge funds, investment banks, financial research firms

While both roles involve quantitative skills and programming, the Home Based High Frequency Trading Software Engineer focuses on developing trading algorithms and software, whereas the Home Based Quantitative Analyst emphasizes data analysis and modeling to inform trading strategies.

What are some common challenges faced by home-based high frequency trading (HFT) software engineers, and how can they be addressed?

Home-based HFT software engineers often face challenges related to maintaining low-latency connectivity and real-time collaboration with team members. Working remotely requires setting up a robust and secure home network to ensure reliable access to trading infrastructure. Additionally, staying updated with the latest financial regulations and technology advancements is crucial. Effective communication tools and regular virtual meetings help foster collaboration, while a disciplined work routine aids in managing the fast-paced and high-pressure nature of HFT environments.

What are the key skills and qualifications needed to thrive as a Home Based High Frequency Trading Software Engineer, and why are they important?

To thrive as a Home Based High Frequency Trading Software Engineer, you need advanced programming skills (especially in C++, Python, or Java), deep knowledge of algorithms, and a solid background in computer science or a related field. Familiarity with low-latency systems, networking protocols, and trading platforms, as well as experience with Linux and version control systems, are typically required; certifications in financial technology or quantitative analysis can be advantageous. Strong problem-solving abilities, attention to detail, self-motivation, and effective remote communication skills set top professionals apart in this field. These skills and qualities are crucial to designing, optimizing, and maintaining robust trading systems that compete effectively in fast-moving financial markets.

What are Home Based High Frequency Trading Software Engineers?

Home Based High Frequency Trading (HFT) Software Engineers are specialized developers who design, build, and maintain software systems that execute large volumes of financial trades at extremely high speeds, all while working remotely. These engineers focus on optimizing algorithms for speed and reliability, often working with low-latency systems, networking, and real-time data processing. They collaborate closely with quantitative analysts and traders to implement trading strategies and ensure the software complies with regulatory standards. Working from home, they use secure and robust remote access tools to connect to financial markets and development environments.
More about Home Based High Frequency Trading Software Engineer jobs
What cities are hiring for Home Based High Frequency Trading Software Engineer jobs? Cities with the most Home Based High Frequency Trading Software Engineer job openings:
What are the most commonly searched types of High Frequency Trading Software Engineer jobs? The most popular types of High Frequency Trading Software Engineer jobs are:
What states have the most Home Based High Frequency Trading Software Engineer jobs? States with the most job openings for Home Based High Frequency Trading Software Engineer jobs include:
What job categories do people searching Home Based High Frequency Trading Software Engineer jobs look for? The top searched job categories for Home Based High Frequency Trading Software Engineer jobs are:
Infographic showing various Home Based High Frequency Trading Software Engineer job openings in the United States as of June 2026, with employment types broken down into 81% Full Time, and 19% Part Time. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $147,524 per year, or $70.9 per hour.
Machine Learning Engineer

Machine Learning Engineer

Point72

New York, NY • On-site

Full-time

Posted 29 days ago


Job description

About Cubist
Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources.
Role/Responsibilities:
We are seeking a Machine Learning Engineer to join the High Frequency Trading Technology team.
This role will apply the latest AI technologies to solve various real-world problems and streamline day-to-day operations, such as creating a production support AI agent that helps monitor production problems and suggest actions.
This role will also work with the AI research group on various projects such as creating synthetic data for training and using MCP agents to streamline research workflow.
Requirements:
  • PhD or PhD candidate in machine learning, computer science or other AI related research fields
  • Experience with sequential modeling and time series forecasting using deep learning
  • Experience with deep neural networks and representation learning
  • Prior experience working in a data driven research environment
  • Experience with translating mathematical models and algorithms into code
  • Proficiency in programming languages such as Python and R
  • Experience with machine learning software libraries such as TensorFlow or PyTorch
  • Experience implementing Agent or Context engineering is strongly preferred
  • Experience with natural language processing technology is strongly preferred
  • Excellent analytical skills, with strong attention to detail
  • Collaborative mindset with strong independent research ability
  • Strong written and verbal communication skills
  • Commitment to the highest ethical standards