Data Scientist / ML Engineer (Antarctica Capital)

OPPORTUNITY
We are seeking a highly skilled Data Scientist / Machine Learning Engineer to help design, build, deploy, and maintain scalable machine learning systems within Antarctica Capital as part of the Octantis platform. A key initial area of focus for this role will be deep collaboration with the architect/author of an existing neural network used to predict risk factors associated with bonds. In this capacity you will develop an understanding of the existing modeling techniques; identify opportunities for improvement across model performance, infrastructure, reliability, and cost; and lead implementation of those improvements.

Beyond the initial focus area, this role will have significant opportunities to deliver impactful, value-generating capabilities within the firm and a fast, flexible, agile team on which to work.

KEY RESPONSIBILITIES:

Refactor Neural Network

• Collaborate with architect and author of neural network bond risk product to identify areas for improvement.
• Lead architecture and development effort

Ongoing

• Contribute to the design, development, and deployment of firm-wide architecture, norms, policies, infrastructure and methodologies for machine learning activities across multiple company groups.
• Design, develop, and deploy machine learning models into production environments.
• Collaborate with data scientists to translate prototypes into production-ready systems.
• Build and maintain data pipelines, feature stores, and model-serving infrastructure.
• Evaluate and optimize model performance, latency, and scalability.
• Implement automated training, testing, and deployment workflows (MLOps).
• Monitor models in production and address issues related to drift, performance degradation, or data quality.
• Conduct code reviews and ensure best practices in ML engineering and software development.
• Stay current with emerging ML/AI technologies and recommend tools or frameworks that improve team efficiency.

Other Duties as Assigned

EXPERIENCE

• 7+ years building machine learning models with Python and AWS.
• Hands-on experience with ML frameworks such as Pytorch and TensorFlow.
• Experience with ML observability and training platforms/technologies like ML Flow.
• Proficiency in building and deploying models using cloud platforms such as AWS (e.g. in Fargate)
• Solid understanding of algorithms, data structures, and software engineering principles.

Preferred:

• Experience with data and compute orchestration tools like AWS Step Functions or Apache Airflow.
• Exposure to large scale data warehousing and query engine technologies like Iceberg and Athena, and to columnar data storage formats like parquet.
• Experience working with and modernizing legacy software, including migrating from on-prem to cloud-based deployments.

SKILLS / KNOWLEDGE

Core Technical Skills (Required):

• Tensorflow, Pytorch
• Python, Pydantic
• AWS Lambda, Fargate, Step Functions, other usual suspects
• IaC / CDK Additional Technical Skills

(Highly Valued):

• API development with FastAPI 

WORKING ENVIRONMENT

• Fully remote role open to individuals located in and working from the U.S. and Canada.
• Agile software development with daily standups and weekly Scrum cadence.
• Fast-paced environment with need to adapt quickly to time-sensitive deliveries.
• Working hours: 9:00 AM – 5:00 PM Central Time Monday through Friday (except recognized holidays); be available for a minimum of six (6) hours daily during this period to facilitate collaboration.

YOUR COMPENSATION
Base Salary Range: $145,000-$170,000 CAD annually. This range is based on Vancouver, BC-derived compensation for this role and may differ for other geographies. The selected candidate's compensation will be determined based on multiple factors, including but not limited to job-related skills, experience, education, and location.