Job description

Voleon is a technology company that applies state-of-the-art machine learning techniques to real-world problems in finance. For more than a decade, we have led our industry and worked at the frontier of applying machine learning to investment management. We have become a multibillion-dollar asset manager, and we have ambitious goals for the future. As a Staff Software Engineer on the Batch and Realtime Streaming team, you will play a pivotal role in architecting, developing, and maintaining Voleon’s Batch and Realtime Streaming platform—the essential data backbone that powers our machine learning research and production trading systems. You will collaborate closely with researchers and finance professionals to design high-performance interfaces and tools that streamline feature productization, discovery, access, and management. This is an opportunity to make a significant impact at the intersection of cutting-edge technology and quantitative finance. YOUR TEAM We seek exceptional individuals who are driven by curiosity and a passion for tackling complex problems through innovation and solid engineering principles. At Voleon, you’ll join a collaborative culture where creative ideas are encouraged, experimentation is celebrated, and efficient execution is valued. You’ll work shoulder-to-shoulder with seasoned engineers who’ve joined us from top technology firms and leading academic institutions. Together, you’ll partner with world-class machine learning researchers, including internationally recognized leaders in artificial intelligence and machine learning, as well as accomplished professionals in both finance and technology. Beyond our vibrant and intellectually stimulating environment, we offer highly competitive compensation and benefits packages, regular technology talks led by our in-house experts, a state-of-the-art modern office, daily catered lunches, and much more. RESPONSIBILITIES - Architect, design, and implement core components for a Batch and Realtime Streaming platform, including data ingestion pipelines, storage systems, serving layers, and API interfaces - Ship new features by collaborating across research, legal, trading, finance operations data, and infra teams for trading systems - Collaborate with ML researchers and data scientists to understand their workflows and design intuitive interfaces (APIs, SDKs, UIs) for seamless feature discovery, access, and reuse - Ensure data quality, consistency, and lineage for features, building robust mechanisms for versioning, monitoring, and governance - Optimize data pipelines and storage for high performance, scalability, and reliability, considering both batch and real-time use cases - Drive adoption of the feature store across teams by producing documentation, onboarding materials, and developer support - Mentor junior engineers and contribute to team best practices and technical excellence REQUIREMENTS - Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field (or equivalent experience) - 10+ years of software engineering experience, with a strong background in distributed computing and data infrastructure - Experience in programming languages such as Python and Go - Understanding of database technologies (Postgres, MySQL, Cassandra, DuckDB) and experience with APIs (REST/gRPC) - Strong problem-solving skills, with a focus on delivering high-quality, maintainable, and well-documented solutions - Excellent communication and collaboration skills; ability to work closely with both engineering and research teams Preferred Qualifications - Experience building large-scale data pipelines and storage systems (e.g., Airflow, Spark, Ray, Iceberg, etc) - Exposure to modern Python data science tooling. (pandas, polars, dask, duckdb, etc) - Experience with monitoring and observability tools for distributed systems (e.g., Prometheus, Grafana, ELK Stack) - Prior experience working with feature stores (e.g., Feast, Hopsworks, or custom solutions) is highly desirable “FRIENDS OF VOLEON” CANDIDATE REFERRAL PROGRAM If you have a great candidate in mind for this role and would like to have the potential to earn $15,000 if your referred candidate is successfully hired and employed by The Voleon Group, please use this form voleon.com to submit your referral. For more details regarding eligibility, terms and conditions please make sure to review the Voleon Referral Bonus Program voleon.com. EQUAL OPPORTUNITY EMPLOYER The Voleon Group is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law.

Requirements

Must-haves

Architect, design, and implement core components for a Batch and Realtime Streaming platform, including data ingestion pipelines, storage systems, serving layers, and API interfaces
Ship new features by collaborating across research, legal, trading, finance operations data, and infra teams for trading systems
Collaborate with ML researchers and data scientists to understand their workflows and design intuitive interfaces (APIs, SDKs, UIs) for seamless feature discovery, access, and reuse
Ensure data quality, consistency, and lineage for features, building robust mechanisms for versioning, monitoring, and governance
Optimize data pipelines and storage for high performance, scalability, and reliability, considering both batch and real-time use cases
Drive adoption of the feature store across teams by producing documentation, onboarding materials, and developer support
Mentor junior engineers and contribute to team best practices and technical excellence
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field (or equivalent experience)
10+ years of software engineering experience, with a strong background in distributed computing and data infrastructure
Experience in programming languages such as Python and Go
Understanding of database technologies (Postgres, MySQL, Cassandra, DuckDB) and experience with APIs (REST/gRPC)
Strong problem-solving skills, with a focus on delivering high-quality, maintainable, and well-documented solutions
Excellent communication and collaboration skills; ability to work closely with both engineering and research teams

Nice-to-haves

Experience building large-scale data pipelines and storage systems (e.g., Airflow, Spark, Ray, Iceberg, etc)
Exposure to modern Python data science tooling. (pandas, polars, dask, duckdb, etc)
Experience with monitoring and observability tools for distributed systems (e.g., Prometheus, Grafana, ELK Stack)
Prior experience working with feature stores (e.g., Feast, Hopsworks, or custom solutions) is highly desirable

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningapimlpythongopostgresrest

Platform: ashby
Effort: quick