The Voleon Group

Senior / Staff Software Engineer - Batch and Realtime Streaming

Berkeley, California, United States

Not SpecifiedCompensation
Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level
Full TimeJob Type
UnknownVisa
Biotechnology, Finance, Artificial Intelligence, AI & Machine Learning, Asset ManagementIndustries

Senior/Staff Software Engineer, Batch and Realtime Streaming

Employment Type: Full-time

Position Overview

Voleon is a technology-driven firm at the forefront of applying advanced AI and machine learning to solve real-world challenges in finance. For over a decade, we have been industry leaders, pioneering the use of AI/ML in investment management. Our continued innovation has established us as a multibillion-dollar asset manager with ambitious plans for the future.

As a Senior/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).
  • 5+ years of software engineering experience, with a strong background in backend systems, distributed computing, or data infrastructure.
  • Experience in programming languages such as Python, Go, and C++.
  • Understanding of database technologies (Postgres, MySQL, Cassandra, DynamoDB, SQLite, DuckDB or MongoDB) 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, etc.).
  • Exposure to modern Python data science tooling (pandas, polars, dask, duckdb, etc.).
  • Experience with monitoring and observability tools for distributed systems.

Company Information

Voleon is a technology-driven firm at the forefront of applying advanced AI and machine learning to solve real-world challenges in finance. For over a decade, we have been industry leaders, pioneering the use of AI/ML in investment management. Our continued innovation has established us as a multibillion-dollar asset manager with ambitious plans for the future.

Skills

AI
Machine Learning
Batch Processing
Realtime Streaming
Data Architecture
Software Development
High-Performance Interfaces
Feature Engineering
Quantitative Finance

The Voleon Group

Investment management using machine learning algorithms

About The Voleon Group

Voleon focuses on investment management by utilizing machine learning to analyze financial market trends. The firm uses advanced statistical models to process large datasets and identify patterns that inform investment decisions, setting it apart from traditional methods that rely on human intuition. Voleon serves institutional clients and operates on a performance-based fee structure, aligning its interests with those of its clients. The company's goal is to provide data-driven insights that optimize investment returns while adapting to changing market conditions.

Berkeley, CaliforniaHeadquarters
2007Year Founded
VENTURE_UNKNOWNCompany Stage
Quantitative Finance, Financial ServicesIndustries
51-200Employees

Benefits

Health Insurance
Dental Insurance
Vision Insurance
Life Insurance
Paid Vacation
Paid Sick Leave
401(k) Retirement Plan
401(k) Company Match

Risks

Competition from other quantitative hedge funds may erode Voleon's market share.
Regulatory scrutiny on AI use in finance could increase compliance costs for Voleon.
Data quality issues could lead to inaccurate predictions and financial losses for Voleon.

Differentiation

Voleon uses machine learning for data-driven financial market predictions.
The firm serves institutional clients with a focus on scalability and risk management.
Voleon's academic approach emphasizes intellectual rigor and continuous learning.

Upsides

Increased interest in ESG investing offers new opportunities for Voleon's models.
Alternative data sources enhance predictive models for quantitative hedge funds like Voleon.
Cloud computing enables efficient scaling of Voleon's data processing capabilities.

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