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Data Scientist / ML Engineer (Antarctica Capital)
This a Full Remote job, the offer is available from: United States
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:
- Collaborate with architect and author of neural network bond risk product to identify areas for improvement.
- Lead architecture and development effort
- 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.
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.
- 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.
