Join the High Frequency Trading Technology team (Cubist) to apply state-of-the-art AI to production and research problems. You will build production AI agents to monitor and suggest actions for operational issues, and collaborate with the AI research group on projects like synthetic data generation and MCP agents to streamline research workflows. The role requires translating mathematical models into production code and working with sequential modeling, time series forecasting, and representation learning. Strong research background and proficiency in Python/R and ML frameworks (TensorFlow/PyTorch) are expected.
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
The annual base salary range for this role is $150,000-$200,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.
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Role/Responsibilities:
\n
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:
\n
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
The annual base salary range for this role is $150,000-$200,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.
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Join the High Frequency Trading Technology team (Cubist) to apply state-of-the-art AI to production and research problems. You will build production AI agents to monitor and suggest actions for operational issues, and collaborate with the AI research group on projects like synthetic data generation and MCP agents to streamline research workflows. The role requires translating mathematical models into production code and working with sequential modeling, time series forecasting, and representation learning. Strong research background and proficiency in Python/R and ML frameworks (TensorFlow/PyTorch) are expected.
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
The annual base salary range for this role is $150,000-$200,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.
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Role/Responsibilities:
\n
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:
\n
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
The annual base salary range for this role is $150,000-$200,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.
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