ML Engineer

• Collaborate with Engineering and Product to leverage data to comprehend business customer challenges
• Demonstrate a value-delivery perspective
• Create trials with predetermined results that stakeholders have approved
• Utilize best practices and cutting-edge tools to minimize waste and faults while maintaining a delivery-focused approach
• Experiments and methods to improve prediction quality should be implemented to improve product performance
• Conduct experiments with machine learning approaches and demonstrate or refute their applicability to the performance of the product
• Assist engineering in implementing novel production procedures
• Put strategies into action to enhance model deployment, performance tracking, and further MLOps projects

Job Requirements:

• Bachelor s/Master s degree in Engineering, Statistics, Informatics, Information Systems, Computer Science (or equivalent experience)
• At least 4 years of relevant experience as an ML Engineer
• Prolific experience working with Snowflake, Airflow, and AWS
• Strong understanding of ML models and their applications
• Demonstrable experience working with Python, Machine Learning, and Data Science libraries
• Extensive experience working with Data wrangling and associated SQL skillset
• Solid experience with feature extraction and engineering
• Experience overseeing projects from requirement collection to completion
• Previous experience in an early-stage startup and experience scaling data processes
• Strong knowledge of tools and the pros and cons of building versus purchasing in order to solve issues related to coordinating the execution of tasks, deploying models, monitoring performance, etc.
• Prior full-stack machine learning experience and the ability to define problems and carry them out through production deployment
• Some prior expertise with stream-processing systems and creating and managing a data pipeline from scratch is nice to have
• Thorough understanding of the Snowflake/Kafka experience in particular
• Extensive knowledge of data input and orchestration tools (such as Airflow, Airbyte, Flyte, etc.) is desirable
• Strong background using Data Transformation Tooling (DBT) and proficient knowledge of AWS is preferred
• Excellent English communication skills, both spoken and written