Machine Learning Engineer

Canvas Fundamental Research Group; New York (NY); On-site; USD 150,000 - 200,000; Full time

Job summary

Canvas Fundamental Research Group in New York is seeking a Machine Learning Engineer to join the High Frequency Trading Technology team, applying state-of-the-art AI to real-world problems and building a production AI agent to monitor production issues and suggest actions.

You will collaborate with the AI research group on projects like synthetic data creation and MCP agents to streamline research workflows; required PhD or candidate status, expertise in sequential modeling, time series

Qualifications

• 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.

Responsibilities

• 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.

Skills

Sequential modeling

Time series forecasting

Deep learning

Python

R

NLP

Research in data-driven environments

Strong communication

Education

PhD in machine learning / CS

PhD candidate

Tools

TensorFlow

PyTorch

Job description

Experience

Early Career

Location

New York

Focus

Systematic Investing

Business

Cubist

Role/Responsibilities

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.