Machine Learning Engineer, Data Products (Remote)
Brex (View all Jobs)
Canada
Interview Process
1. Practical questions - 1 hour technical 2. Then 4-5 hour onsite. System design, Coding, values, debugging
Programming Languages Mentioned
Python, Java, C++, SQL
Why join us
Brex empowers the next generation of businesses with an integrated corporate card and spend management software. We make it easy for our customers to manage every aspect of spending and empower their employees to make better financial decisions from anywhere they live or work. Brex proudly serves tens of thousands of growing businesses, from early-stage startups to enterprise leaders.
Working at Brex allows you to push your limits, challenge the status quo, and collaborate with some of the brightest minds in the industry. We’re committed to building a diverse team and inclusive culture and believe your potential should only be limited by how big you can dream. We make this a reality by empowering you with the tools, resources, and support you need to grow your career.
Machine Learning at Brex
The Data Science ML teams build automated data-driven solutions with machine learning & AI to help optimize business decisions for internal customers and to empower and delight our growing external customers, while protecting Brex. We are fully embedded into our business functions to drive towards the same goals, while also keeping a data science community where we learn from each other and collaborate on various DS initiatives.
What you’ll do
As an MLE on the Data Products team, you will collaborate with our Engineering, Products, and Design teams to identify customer pain points, develop and deploy machine learning models to convert them to delightful customer experiences.
Responsibilities
- Apply your expertise in quantitative analysis, machine learning, and software engineering to build scalable and robust batch and real-time ML models from end to end.
- Collaborate with cross-functional teams to unravel complex problems by clearly formulating the problem statement, understanding technical requirements, and presenting findings at all levels.
- Maintain a strong data driven culture within the company by interacting with diverse internal functions.
Requirements
- 4+ years in a Data Science / ML Engineering/ Software Engineering role
- Experience in the end to end machine learning model development cycles, including model productionization and management.
- Strong interpersonal and communication skills and having worked with different business functions.
- Proficiency in Python, and/or other backend programming languages (C++, Java, Kotlin,)
- Proficiency in SQL or NoSQL databases
- Experience with data pipelines and data warehousing, such as Airflow and Snowflake or equivalent tools and frameworks.
Bonus points
- A MS or Ph.D. degree in a quantitative field (e.g. stats, physics, computer science)
- Understands various tradeoffs in machine learning deployment such as computation optimization, performance requirements, latency and data quality assurance.
- Experience with deep learning (NLP, computer vision, etc.)
- Experience in deploying/managing/interacting with microservices, event-streaming pipeline and data intensive applications.
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