The Voleon Group
New York City, New York
Job DescriptionJob DescriptionVoleon is a quantitative hedge fund that uses machine learning as its core investment approach across a wide range of regions and asset classes. Voleon is a multibillion-dollar asset manager where the size of the engineering organization still allows for direct influence across key systems. Strategy Platform owns the infrastructure between quantitative research and live trading. Our systems orchestrate the transformation of external market data into features consumed by ML-driven trading strategies, manage strategy deployments from research handoff through production, and provide the tooling that lets researchers iterate quickly without compromising production reliability. This is a central platform team. We are consolidating and unifying systems that grew organically to serve different parts of the trading lifecycle, building and migrating to shared abstractions across data ingestion, feature computation, deployment and production trading operations. The team balances deep knowledge of how our trading strategies operate with building foundational layers that support the company's continued rapid growth.The RoleYou will own significant pieces of our platform end to end: designing, building, operating, and evolving them. Concretely: Own how data is accessed, validated, orchestrated, and catalogued across research and production Engineer smooth deployment processes for research experiments into production Develop tooling to integrate data from diverse vendors, unifying symbol mappings for data consistency Support data pipelines with strong temporal semantics under a range of latency and correctness requirements Sequence platform migrations that move the firm toward shared abstractions while minimizing disruption to active trading systems Lead complex projects spanning the company, collaborating across research, legal, trading, finance operations, data, and infrastructure teams Build tooling to support integration with new assets and markets Improve observability across the strategy lifecycle, including data cataloguing, experiment tracking, and production SLAs You might be a good fit if you have: 5+ years of experience in backend, data pipelines, or platform engineering Owned platform systems that other teams depend on daily, made real decomposition decisions (data access layers, API versioning, data models, migration sequencing), and improved those systems while they were actively in use Strong debugging and observability instincts. You orient quickly in unfamiliar codebases and datasets, particularly across data pipelines with many upstream sources and downstream consumers Computer Science Degree, or equivalent experience Preferred Qualifications Experience with Airflow, Dagster, Spark, Iceberg, Trino, Flink, or similar data infrastructure Familiarity with ML infrastructure patterns (feature stores, model serving, experiment tracking) Python Fluency Compensation The base salary range for this position is $270,000 to $300,000 in the location(s) of this posting. Individual salaries are determined through a variety of factors, including, but not limited to, education, experience, knowledge, skills, and geography. Base salary does not include other forms of total compensation, such as bonus compensation and other benefits. Our benefits package includes medical, dental, and vision coverage, life and AD&D insurance, 20 days of paid time off, 9 sick days, and a 401(k) plan with a company match. "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 to submit your referral. For more details regarding eligibility, terms, and conditions, please make sure to review the Voleon Referral Bonus Program. 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. We may use artificial intelligence (AI) tools to support parts of the hiring process. These tools assist our recruitment team but do not replace human judgement. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
Job DescriptionJob DescriptionVoleon is a quantitative hedge fund that uses machine learning as its core investment approach across a wide range of regions and asset classes. Voleon is a multibillion-dollar asset manager where the size of the engineering organization still allows for direct influence across key systems. Strategy Platform owns the infrastructure between quantitative research and live trading. Our systems orchestrate the transformation of external market data into features consumed by ML-driven trading strategies, manage strategy deployments from research handoff through production, and provide the tooling that lets researchers iterate quickly without compromising production reliability. This is a central platform team. We are consolidating and unifying systems that grew organically to serve different parts of the trading lifecycle, building and migrating to shared abstractions across data ingestion, feature computation, deployment and production trading operations. The team balances deep knowledge of how our trading strategies operate with building foundational layers that support the company's continued rapid growth.The RoleYou will own significant pieces of our platform end to end: designing, building, operating, and evolving them. Concretely: Own how data is accessed, validated, orchestrated, and catalogued across research and production Engineer smooth deployment processes for research experiments into production Develop tooling to integrate data from diverse vendors, unifying symbol mappings for data consistency Support data pipelines with strong temporal semantics under a range of latency and correctness requirements Sequence platform migrations that move the firm toward shared abstractions while minimizing disruption to active trading systems Lead complex projects spanning the company, collaborating across research, legal, trading, finance operations, data, and infrastructure teams Build tooling to support integration with new assets and markets Improve observability across the strategy lifecycle, including data cataloguing, experiment tracking, and production SLAs You might be a good fit if you have: 5+ years of experience in backend, data pipelines, or platform engineering Owned platform systems that other teams depend on daily, made real decomposition decisions (data access layers, API versioning, data models, migration sequencing), and improved those systems while they were actively in use Strong debugging and observability instincts. You orient quickly in unfamiliar codebases and datasets, particularly across data pipelines with many upstream sources and downstream consumers Computer Science Degree, or equivalent experience Preferred Qualifications Experience with Airflow, Dagster, Spark, Iceberg, Trino, Flink, or similar data infrastructure Familiarity with ML infrastructure patterns (feature stores, model serving, experiment tracking) Python Fluency Compensation The base salary range for this position is $270,000 to $300,000 in the location(s) of this posting. Individual salaries are determined through a variety of factors, including, but not limited to, education, experience, knowledge, skills, and geography. Base salary does not include other forms of total compensation, such as bonus compensation and other benefits. Our benefits package includes medical, dental, and vision coverage, life and AD&D insurance, 20 days of paid time off, 9 sick days, and a 401(k) plan with a company match. "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 to submit your referral. For more details regarding eligibility, terms, and conditions, please make sure to review the Voleon Referral Bonus Program. 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. We may use artificial intelligence (AI) tools to support parts of the hiring process. These tools assist our recruitment team but do not replace human judgement. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
The Voleon Group
New York City, New York
Job DescriptionJob Description Voleon is a quantitative hedge fund that uses machine learning as its core investment approach across a wide range of regions and asset classes. Voleon is a multibillion-dollar asset manager where the size of the engineering organization still allows for direct influence across key systems. Strategy Platform owns the infrastructure between quantitative research and live trading. Our systems orchestrate the transformation of external market data into features consumed by ML-driven trading strategies, manage strategy deployments from research handoff through production, and provide the tooling that lets researchers iterate quickly without compromising production reliability. This is a central platform team. We are consolidating and unifying systems that grew organically to serve different parts of the trading lifecycle, building and migrating to shared abstractions across data ingestion, feature computation, deployment and production trading operations. The team balances deep knowledge of how our trading strategies operate with building foundational layers that support the company's continued rapid growth. The Role:You will own significant pieces of our platform end to end: designing, building, operating, and evolving them. Concretely: Own how data is accessed, validated, orchestrated, and catalogued across research and production Engineer smooth deployment processes for research experiments into production Develop tooling to integrate data from diverse vendors, unifying symbol mappings for data consistency Support data pipelines with strong temporal semantics under a range of latency and correctness requirements Sequence platform migrations that move the firm toward shared abstractions while minimizing disruption to active trading systems Lead complex projects spanning the company, collaborating across research, legal, trading, finance operations, data, and infrastructure teams Build tooling to support integration with new assets and markets Improve observability across the strategy lifecycle, including data cataloguing, experiment tracking, and production SLAs You might be a good fit if you have: 5+ years of experience in backend, data pipelines, or platform engineering Owned platform systems that other teams depend on daily, made real decomposition decisions (data access layers, API versioning, data models, migration sequencing), and improved those systems while they were actively in use Strong debugging and observability instincts. You orient quickly in unfamiliar codebases and datasets, particularly across data pipelines with many upstream sources and downstream consumers Computer Science Degree, or equivalent experience Preferred Qualifications Experience with Airflow, Dagster, Spark, Iceberg, Trino, Flink, or similar data infrastructure Familiarity with ML infrastructure patterns (feature stores, model serving, experiment tracking) Python Fluency Compensation The base salary range for this position is $225,000 to $255,000 in the location(s) of this posting. Individual salaries are determined through a variety of factors, including, but not limited to, education, experience, knowledge, skills, and geography. Base salary does not include other forms of total compensation, such as bonus compensation and other benefits. Our benefits package includes medical, dental, and vision coverage, life and AD&D insurance, 20 days of paid time off, 9 sick days, and a 401(k) plan with a company match. "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 to submit your referral. For more details regarding eligibility, terms, and conditions, please make sure to review the Voleon Referral Bonus Program. 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. We may use artificial intelligence (AI) tools to support parts of the hiring process. These tools assist our recruitment team but do not replace human judgement. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
Job DescriptionJob Description Voleon is a quantitative hedge fund that uses machine learning as its core investment approach across a wide range of regions and asset classes. Voleon is a multibillion-dollar asset manager where the size of the engineering organization still allows for direct influence across key systems. Strategy Platform owns the infrastructure between quantitative research and live trading. Our systems orchestrate the transformation of external market data into features consumed by ML-driven trading strategies, manage strategy deployments from research handoff through production, and provide the tooling that lets researchers iterate quickly without compromising production reliability. This is a central platform team. We are consolidating and unifying systems that grew organically to serve different parts of the trading lifecycle, building and migrating to shared abstractions across data ingestion, feature computation, deployment and production trading operations. The team balances deep knowledge of how our trading strategies operate with building foundational layers that support the company's continued rapid growth. The Role:You will own significant pieces of our platform end to end: designing, building, operating, and evolving them. Concretely: Own how data is accessed, validated, orchestrated, and catalogued across research and production Engineer smooth deployment processes for research experiments into production Develop tooling to integrate data from diverse vendors, unifying symbol mappings for data consistency Support data pipelines with strong temporal semantics under a range of latency and correctness requirements Sequence platform migrations that move the firm toward shared abstractions while minimizing disruption to active trading systems Lead complex projects spanning the company, collaborating across research, legal, trading, finance operations, data, and infrastructure teams Build tooling to support integration with new assets and markets Improve observability across the strategy lifecycle, including data cataloguing, experiment tracking, and production SLAs You might be a good fit if you have: 5+ years of experience in backend, data pipelines, or platform engineering Owned platform systems that other teams depend on daily, made real decomposition decisions (data access layers, API versioning, data models, migration sequencing), and improved those systems while they were actively in use Strong debugging and observability instincts. You orient quickly in unfamiliar codebases and datasets, particularly across data pipelines with many upstream sources and downstream consumers Computer Science Degree, or equivalent experience Preferred Qualifications Experience with Airflow, Dagster, Spark, Iceberg, Trino, Flink, or similar data infrastructure Familiarity with ML infrastructure patterns (feature stores, model serving, experiment tracking) Python Fluency Compensation The base salary range for this position is $225,000 to $255,000 in the location(s) of this posting. Individual salaries are determined through a variety of factors, including, but not limited to, education, experience, knowledge, skills, and geography. Base salary does not include other forms of total compensation, such as bonus compensation and other benefits. Our benefits package includes medical, dental, and vision coverage, life and AD&D insurance, 20 days of paid time off, 9 sick days, and a 401(k) plan with a company match. "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 to submit your referral. For more details regarding eligibility, terms, and conditions, please make sure to review the Voleon Referral Bonus Program. 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. We may use artificial intelligence (AI) tools to support parts of the hiring process. These tools assist our recruitment team but do not replace human judgement. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.