Creating scalable machine learning solutions and contributing to best practices as a Senior Engineer at Thomson Reuters. Collaborating with cross-functional teams for impactful project implementation.
Responsibilities
Be part of the development and technical implementation of machine learning solutions
Create machine learning solutions that are scalable, dependable, and secure
Craft and sustain technical outputs such as design documentation and representative models
Contribute to the establishment of machine learning best practices and quality control, including code reviews
Requirements
At least 2 years of experience in addressing practical machine learning challenges, particularly with Recommender Systems
A profound comprehension of data processing, machine learning infrastructure, and DevOps/MLOps practices
A minimum of 2 years of experience with cloud technologies (AWS SageMaker, AWS is preferred)
Direct experience in machine learning and orchestration, developing intricate multi-tenant machine learning products
Strong Python programming skills is required, SQL, and data modeling expertise, with DBT considered a plus
Familiarity with Spark, Airflow, PyTorch, Scikit-learn, Pandas, Keras, and other relevant ML libraries
Experience in leading and supporting engineering teams
Robust background in crafting data science and machine learning solutions
A creative, resourceful, and effective problem-solving approach
Benefits
Hybrid Work Model: Flexible hybrid working environment (2-3 days a week in the office)
Flexibility & Work-Life Balance: Work from anywhere for up to 8 weeks per year
Career Development and Growth: Continuous learning and skills-first approach
Industry Competitive Benefits: Comprehensive benefit plans including flexible vacation, two company-wide Mental Health Days off, access to Headspace app, retirement savings, tuition reimbursement, employee incentive programs, and resources for mental, physical, and financial wellbeing
Culture: Award-winning reputation for inclusion and belonging, flexibility, work-life balance
Social Impact: Two paid volunteer days off annually and opportunities to get involved with pro-bono consulting projects and ESG initiatives
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