Rokt is looking to solve business challenges including smart bidding, budget pacing, lookalike modeling, and more, by designing, building and production-ising proprietary machine learning models
Requirements
- Masters or PhD in Machine Learning
- 10+ years of industry experience in building production-grade machine learning systems with all aspects of model training, tuning, deploying, serving and monitoring
- Deep Knowledge in AWS, Kubeflow (or similar), Tensorflow and Feature Store in a production environment
- Deep 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
- 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 and ESMM
- Experience with machine learning and software engineering
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
Other
- Masters or PhD degree
- 10+ years of industry experience
- Ability to work in a team and collaborate with others
- Excellent communication and presentation skills
- Ability to work in a fast-paced environment and adapt to changing priorities
