As a Senior Machine Learning Engineer, you will be part of an Agile team dedicated to scaling machine learning applications.
You will focus on architectural design, model and application code development, and ensuring high availability and performance of machine learning applications.
Additionally, you will have the opportunity to learn and apply the latest innovations and best practices in machine learning engineering.
- Design, build, and deliver ML models and components to solve real-world business problems in collaboration with Product and Data Science teams.
- Use your understanding of ML modeling techniques to inform infrastructure decisions.
- Write and test application code, develop and validate ML models, and automate tests and deployment to solve complex problems.
- Collaborate as part of a cross-functional Agile team to create and enhance software for big data and ML applications.
- Retrain, maintain, and monitor models in production.
- Leverage or build cloud-based architectures, technologies, and platforms to deliver optimized ML models at scale.
- Construct optimized data pipelines to feed ML models.
- Implement continuous integration and deployment best practices to ensure successful deployment of ML models and application code.
- Ensure code is well-managed to reduce vulnerabilities and models follow best practices in Responsible and Explainable AI.
- Use programming languages like Python, Scala, or Java.
Basic Qualifications :
- Bachelor's degree
- At least 4 years of experience programming with Python, Scala, or Java
- At least 3 years of experience designing and building data-intensive solutions using distributed computing
- At least 2 years of on-the-job experience with an industry recognized ML frameworks
- At least 1 year of experience productionizing, monitoring, and maintaining models
Preferred Qualifications :
- Experience building, scaling, and optimizing ML systems
- Experience with data gathering and preparation for ML models
- Experience developing performant, resilient, and maintainable code
- Experience developing and deploying ML solutions in a public cloud such as AWS, Azure, or Google Cloud Platform
- Master's or doctoral degree in computer science, electrical engineering, mathematics, or a similar field
- Experience with distributed file systems or multi-node database paradigms
- Contributed to open source ML software
- Authored / co-authored a paper on a ML technique, model, or proof of concept
- Experience building production-ready data pipelines that feed ML models
- Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating their performance
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