Machine Learning Engineer

Job summary

The Machine Learning Engineer will be responsible for implementing and maintaining data science models in bpx’s machine learning studio. The role will be a subject matter expert in machine learning operations and the associated technology. This role will bridge the gap between pure data science and the computational requirements needed to meet business outcomes. The role will have the ability to guide bpx’s data science journey in a nascent technology stack. The ML Engineer will have significant freedom and latitude to suggest and implement solutions.

Key Accountabilities:

• Implement data science algorithms in bpx’s ML Studio (SageMaker).
• Create systems and processes to monitor performance of ML algorithms in production.
• Serve as the subject matter expert of ML Operations and guides data scientists in the practical implications of model design
• Collaborate with the data engineering team to build and maintain data pipelines from systems like Snowflake and OSI Pi
• Partner with bpx Architecture team to ensure endpoints, compute, and network considerations are built into solutions
• Takes initiative and stays up to date with the latest data science trends, techniques, and best practices, determining how to incorporate the most suitable practices in the department.
• Work as part of geographically dispersed team, effectively communicating prioritized business needs and prioritized project statuses.
• Design systems to balance cost and performance to meet business outcomes

Essential Education:

• A Bachelor’s degree (Master’s preferred) in Statistics, Mathematics, Computer Science, or any other related quantitative field.

Essential Experience and Job Requirements:

• 7+ years in data science or related field, 3+ years of hands on experience in machine learning operations.
• Proven track record of implementing and scaling models in an operations or customers focused company
• Strong programming skills: Python and Cloud Implementation Scripting
• Experience with big data, real-time streaming data technologies, and cluster computing environments.
• Knowledge and exposure to cloud technologies, especially AWS.

We offer a reward and wellbeing package to enable your work to fit with your life. These can include, but not limited to, access to health, vision and dental insurance, flexible working schedule, paid time off policy, discretionary annual bonus program, long-term incentive program, and a generous 401K matching program. How much do we pay (Base)? $106,000-$160,000
*Note that the pay range listed for this position is a good faith and reasonable estimate of the range of possible base compensation at the time of posting.