Lead Machine Learning Engineer

Key Skills

Java Programming, Python Programming, MongoDB, SQL, Azure, AWS, Apache Kafka, Machine learning techniques, Data science techniques, Jenkins, A/B Testing, Apache Cassandra, Apache Airflow, Google Cloud Platform (GCP), Nginx, R Programming, MySQL, Linear Algebra, Amazon RedShift, SPARK Programming, RabbitMQ, Numerical Computing, ElastiCache

Job Description

Our tech stack is hosted on AWS and is built on Cloudfront / AWS API Gateway, NGINX, / Java, Redis / ElastiCache and MySQL / Cassandra as our end to end stack. Besides these, we heavily use MongoDB, Kinesis, Kafka, RabbitMQ, Spark, Redshift and other cutting edge techs to keep improving Dream11's performance. As a data-driven team, we also use R, Python and other big data technologies for Machine Learning and Predictive Analytics.

Your Role:

• Orchestrating online experimentation at scale to provide insights in a standard format for consumption across the company
• Designing and maintaining DAGs which move Machine Learning processes towards continuous experimentation and evaluation
• Performing distributed machine learning training and designing distributed Machine Learning Engineering Pipelines
• Working with platform engineering team in designing API contracts which are scalable for multiple years

Must Have:

• 5+ years of experience as a ML Engineer or Software Engineer or Data Engineer or related fields
• Solid understanding of concepts such as model drift, model validation, continuous ML deployment
• Very good understanding of Distributed ML training and deployment (preferably via Spark, Dask, EMR based setups)
• Experience building modular ML systems that integrate with product

Good to Have:

• Understanding concepts such as cost sensitive learning, tweaking of cost functions, deep learning concepts and implementations
• Ability to implement SOTA ML pipelines/systems described by good papers end to end
• Completed CS 329S: Machine Learning Systems Design course