Remote Jobs at Belvedere Trading

Candidates should possess at least six years of performance engineering experience within trading or a similar field, along with a proven coding ability in C++ or Java as their primary development language, and a strong knowledge of network programming, including raw sockets and latency optimization. They should also have a Bachelor’s or Master’s level degree in Computer Science, Engineering, or a related field, and a desire to continuously learn and proactively improve processes.

Candidates should possess a Bachelor’s degree in Computer Science, Data Science, or a related field, and have at least 5 years of experience as a Data Engineer, with a strong focus on building and maintaining data pipelines and data warehouses. Experience with SQL and NoSQL databases is required, along with proficiency in programming languages such as Python or Java. Familiarity with cloud platforms like AWS or Azure is also desired.

Candidates must possess a Bachelor’s degree in STEM/Finance, Economics, or a related field, and a minimum of 2 years of relevant trading experience, preferably in futures markets. They should demonstrate a deep understanding of futures products and futures exchange market structure, along with advanced computational and quantitative skills, particularly in Python. A proven history of consistent profitability in trading is also required.

Candidates should possess a Bachelor’s degree in Computer Science or a related field, and have at least 7 years of experience in software development, with a focus on high-performance systems. Strong experience with cloud technologies, particularly Google Cloud Platform, is required, as is familiarity with data warehousing and pipeline implementation. Experience with data quality automation and operational oversight is also desired.

Candidates should possess 3-5 years of experience with compiling and deploying software in multiple languages, specifically C++, Python, and Java, along with experience in building and deploying CI/CD systems, infrastructure as code, and build job orchestration. Strong experience with Kubernetes workloads and cloud engineering solutions is also required.

Candidates should possess a Ph.D. in Computer Science, Engineering, Applied Mathematics, or a related quantitative field, along with at least 5 years of experience applying machine learning in feedback-loop systems, robotics, autonomous decision-making, or control systems. Strong knowledge of machine learning algorithms, particularly those related to reinforcement learning, is required, as well as familiarity with dealing with uncertainty in problem statements.

Candidates must possess a Bachelor’s degree in Computer Science, Computer Engineering, Data Science, or Information Science. A minimum of 3 months of internship experience in Python, C++, financial data analysis, and financial modeling is required, or at least 3 credit hours of relevant coursework. Experience with low-latency systems and databases is also necessary.