Senior Software Developer, ML Ops

3 нед. назад

152.9k–189k USD / yearCanadaWorldwideSeniorRemote

machine learningmlopspythonclouddistributed systemsapimonitoring

Senior Software Developer role focused on building machine learning platform services for model training, inference, and operations within a financial tech company.

Обязанности

We are building a multi-product company with a growing offering including Invest, Cash, Crypto, Trade and Tax products.
As a Software Engineer on the Machine Learning Platform team, you will play a pivotal role in our mission to build a self-serve ML Platform to enable data scientists to do their best work. As such, you will work closely with the area owners, data scientists and other software engineers to improve our ML-ops tooling and support the launch of new data products.
- Partner with stakeholders across different product domains, infrastructure to tackle technical problems at scale, which includes building framework agnostic services to support all of 's machine learning needs.
- Establish roadmap and architecture for 's Machine Learning platform
- Build highly performant scalable systems, contributing to our ML platform on Kubernetes and Ray
- Work with a large amount of autonomy to set the technical direction for scalable projects.

Другое

is Canada’s leading financial innovator. The company offers a full suite of simple, sophisticated financial products across managed investing, do-it-yourself trading, cryptocurrency, tax filing, spending and saving. currently serves more than 4 million Canadians and holds over $155 billion in assets under administration. The company was founded in 2014 by a team of financial experts and technology entrepreneurs, and is headquartered in Toronto, Canada.
We're proud of what we've built — and we're just getting started. Read our Culture Manual and learn more about how we work .
The Machine Learning Platform (MLP) team builds the foundation that every ML and GenAI workload at runs on. We partner with data science and engineering teams across the company to take models from experimentation to production reliably and at scale. Our responsibilities are to:
- Build standardized, framework-agnostic services for model training, efficient inference, evaluation and monitoring — across both traditional ML and GenAI
- Provide centralized, governed access to internal and external LLMs
- Set the technical direction for how ML and LLM models are trained, shipped and operated across the company
- 5+ years of experience implementing production-ready services
- 3+ years of experience with python
- 5+ years of software development experience in ML infra, ML tooling or ML engineering
- Proven experience designing and implementing highly performant scalable systems with good observability
- Proven experience owning a project end-to-end and owning and tending complex systems for the long run
- Preferred experience with ML ecosystem (e.g. pytorch, transformers, Ray, feature stores, elastic search and similar vector databases, triton, cuda, DVC, vLLM)
- Kubernetes to orchestrate our services
- FastAPI for RESTful APIs
- MLflow for experiment tracking
- Kubernetes, Ray, Bedrock, vLLM for ML training and inference
- Chronon Feature store
- Kafka, postgres, redshift and snowflake for streaming and data warehousing
🌸 Top-tier health benefits and life insurance
📈 Long-term group savings with employer match, through for Business
🌴 20 vacation days, 4 wellness days, and unlimited sick and mental health days per year
✈️ 90 days away: work outside Canada for up to 90 days per year
👥 Employee resource groups, including Rainbow (2SLGBTQ), Women of WS, and Black at WS
🌎 We are a hybrid team with over 1,500 employees across North America. The people are one of the best parts of working here: you'll collaborate with incredibly talented, curious, and driven teammates who are deeply committed to doing great work.
Technology & Innovation at : We move quickly and build thoughtfully. That means we're always looking for better ways to work — whether that's new tools, AI, or rethinking how we approach a problem. We don't expect you to have all the answers, but we do expect curiosity and a willingness to evolve alongside the products we're building.
Inclusion Statement: We're building products for a diverse world, and we need a diverse team to do it well. We strongly encourage applications from everyone, regardless of race, religion, colour, national origin, gender, sexual orientation, age, marital status, or disability status.
Accessibility Statement: We're committed to an accessible hiring experience. If you need any accommodations throughout the interview process, please let us know — we'll work with you to make sure you have what you need. We also welcome any feedback on how we can better accommodate candidates with accessibility needs.
AI in Hiring: We may use artificial intelligence (AI) tools to support parts of our hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our team but don't replace human judgment – all final hiring decisions are made by people. If you have questions about how your data is used, reach out to us.