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Senior Machine Learning Engineer
| Company | Rokt |
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| Location | San Francisco, CA, USA |
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| Salary | $225000 – $285000 |
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| Type | Full-Time |
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| Degrees | Master’s, PhD |
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| Experience Level | Senior |
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Requirements
- Masters or PhD in Machine Learning
- Extensive knowledge in and experience with some of the following areas – Bayesian methods, Recommender systems, multi-task modelling, meta-learning, click through rate modelling or conversion rate modelling
- 3+ years of industry experience in building production-grade machine learning systems with all aspects of model training, tuning, deploying, serving and monitoring
- Experience with Kubeflow (or similar), Tensorflow and Feature Store in a production environment is a massive plus
Responsibilities
- Collaborate closely with product managers and other engineers to understand business priorities, frame machine learning problems, and architect machine learning solutions
- Build and productionise machine learning models including data preparation/processing pipelines, machine learning orchestrations, improvements of services performance and reliability and etc.
- Contribute and maintain the high quality of the code base with tests that provide a high level of functional coverage as well as non-functional aspects with load testing, unit testing, integration testing, etc.
- Keep track of emerging tech and trends, research the state-of-art deep learning models, prototype new modelling ideas, and conduct offline and online experiments
- Share your knowledge by giving brown bags, tech talks, and evangelising appropriate tech and engineering best practices
Preferred Qualifications
- Bonus points if you are familiar with any of the following architectures or have experience with the models mentioned in this benchmark: DCNV2, MMOE, Deep & Wide, ESMM, xDeepFM, and GDCN
