Senior Machine Learning Scientist

Key Skills

Dask - Python library, Deep Learning, Machine learning techniques, Mentoring, Probability, Python Programming, PyTorch, R Programming, Ray.io, Spark Core, SQL, Statistics, TensorFlow

Job Description

Technology is at the core of everything we do. Our technology team helps us deliver a mobile-first experience across platforms (Android & iOS) while managing over 300 million rpm (requests per minute) at peak with a user concurrency of 10 million.

We have over 150 micro-services written in Java and backed by a Vert.x framework. These work with isolated product features with discrete architectures to cater to the respective use cases.

We work with terabytes of data, the infrastructure for which is built on top of Kafka, Redshift, Spark, Druid, etc. and it powers a number of use cases like Machine Learning and Predictive Analytics. Our tech stack is hosted on AWS, with distributed systems like Cassandra, Aerospike, Akka, Voltdb, Ignite, etc.

Your Role:

• Executing clean experiments rigorously against pertinent performance guardrails and analysing performance metrics to infer actionable findings
• Developing and maintaining services with proactive monitoring and 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 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 of the industry to mentor and guide team members

Qualifiers:

• 3-5 years of experience in building, deploying and maintaining ML solutions
• Extensive experience with Python, Sql, Tensorflow/Pytorch and atleast one distributed data framework (Spark/Ray/Dask )
• Working knowledge of Machine Learning, probability & statistics and Deep Learning Fundamentals
• Experience in designing end to end machine learning systems that work at scale.