onsite
Machine Learning Engineer
Machine Learning Engineer
The Machine Learning Engineer will be responsible for the end-to-end lifecycle of large-scale ML projects, from data preparation and model training to deployment and monitoring. This role involves executing experiments, developing and maintaining services with proactive monitoring, and leveraging a strong foundation in ML, statistics, and deep learning.
About the role
Responsibilities
- Executing clean experiments rigorously against pertinent performance guardrails and analyzing performance metrics to infer actionable findings.
- Developing and maintaining services with proactive monitoring can incorporate best industry practices for optimal service quality and risk mitigation.
- Breaking down complex projects into actionable tasks that adhere to set management practices and ensure stakeholder visibility.
- Managing the end-to-end lifecycle of large-scale ML projects from data preparation, model training, deployment, monitoring, and upgradation of experiments.
- Leveraging a strong foundation in ML, statistics, and deep learning to adeptly implement research-backed techniques for model development.
- Staying abreast of the best ML practices and developments in the industry to mentor and guide team members.
Requirements
- 3-5 years of experience in building, deploying, and maintaining ML solutions.
- Extensive experience with Python, Sql, Tensorflow/Pytorch, and at least one distributed data framework (Spark/Ray/Dask).
- Working knowledge of Machine Learning, probability and statistics, and Deep Learning Fundamentals.
- Experience in designing end-to-end machine learning systems that work at scale.
Skills
PythonSQLTensorFlowPyTorchSparkRayDaskMachine LearningProbabilityStatisticsDeep Learning