Senior Machine Learning Engineer
Confirmed live in the last 24 hours
Development Operations (DevOps)
Google Cloud Platform
- Minimum 5 years experience in data science, software engineering, data engineering or related discipline
- Ability to articulate pros and cons of technical decisions and influence stakeholders
- Strong experience with a suite of cloud DevOps and CI/CD tools (Terraform, Docker, CircleCI, GitHub Actions, Cloud Build, etc) and processes
- Strong Experience with distributed data processing frameworks such as Apache Beam (ie DataFlow), Spark, Flink or similar
- Experience with multiple programming languages - Required: Python, SQL, Nice to Have: Scala, Go, R, C/C++ etc
- Experience with GCP VertexAI, Azure Machine Learning Studio or AWS SageMaker
- Experience with orchestration tools such as Apache Airflow
- Experience in developing real time (RabbitMQ, Kafka, Pub/Sub) and batch pipelines
- Experience with developing, implementing, deploying and scaling machine learning models to production
- Experience in performing root cause analysis of production issues, performance tuning and optimization
- Experience using and extending ML frameworks and libraries (e.g. TensorFlow, PyTorch, scikit-learn, SHAP)
- Experience in healthcare datasets like EMR and Claims and interoperability standards like FHIR
- You should receive a confirmation email after submitting your application
- A recruiter (not a computer) reviews all applications at League
- If we see alignment with League's needs, a recruiter will reach out to learn more about your goals. The recruiter will also share the team-specific interview process depending on the roles you are exploring
- The final step is an offer, which we hope you will accept!
- Prior to joining us, we conduct reference and background checks. Additional checks could be required for US Candidates, depending on the role you are exploring
- Drive architectural choices and develop the League set of MLOps platform tools
- Guide and mentor data scientists and engineers through the MLOps process and framework, including mentoring data scientists in areas such as software development, lifecycle, & data engineering best practices
- Engage in discourse with Data Scientists on trade-offs of deploying various data science models in production
- Translate business and stakeholder needs into MLOps requirements, with attention to details
- Utilize a variety of distributed computing frameworks and cloud services and tools to build scalable ML pipelines and endpoints
- Analyze, tune, troubleshoot and support the MLOps platform ensuring the performance, integrity, and security of data and models produced
- Use sound agile development practices (testing and code reviewing, etc.) to develop and deliver data products
Digital health platform
League is on a mission to power the digital transformation of healthcare. The company is building digital infrastructure for better consumer health experiences.
- Personalized benefits plan
- Health, Lifestyle & Learning spending accounts
- Flexible medical and dental plans
- Fertility treatment support
- Paid parental leave and baby bonus
- Unlimited PTO
- Free mental health counselling and support
- Employee Stock Option Program
- Exclusive access to a curated wellness marketplace
- Sabbatical program
- RRSP/401K accounts
- High-impact onboarding
- Extra-long holiday weekends
- Mental health (wellness) days
Company Core Values
- Creating a healthier future.
- Building a dream team.
- All owners.
- Aspiring to live our best lives.
- In it to win it.