SDE (Machine Learning)


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Technology @Dream11Our Tech Team is the core of Dream11’s mobile-first cross-platform (Android & iOS, Mobile + Desktop PWA) product, serving more than 10 Crore users with over 70 million rpm (requests per minute) at peak with user concurrency of 5.5 million. Our tech stack is hosted on AWS and comprises multiple distributed systems like Cassandra, Aerospike, Akka, Voltdb, Ignite etc.
We have around 100+ micro-services primarily written in Java backed by vert.x framework. They serve isolated product features with discrete architectures to serve the respective use-cases. We have a completely in-house data infrastructure built on top of Kafka, Redshift, Spark, Druid etc. which powers our Machine Learning and Predictive Analytics use-cases. We ingress Terabytes of Data every day, which flows all over our Data pipelines to power a plethora of use-cases. 

Your Role:

  • Scaling Data Science model for serving 100M+ users.
  • Scaling Data Science development lifecycle, Enabling model training and inferencing at scale.
  • Designing robust, scalable platform for enabling Data Science personalised model.
  • Scaling M/L algorithms, processing huge dataset with distributed processing systems like Apache Spark/Apache Flink.
  • Work with the data engineering team to design effective solutions for ETL pipelines and Near real-time data aggregations.
  • Leading cross-functional initiatives and collaborating with engineers across teams.

Must Have:

  • 3+ years experience as Machine Learning Engineer or related field
  • Experience in building batch & streaming applications on platforms like Apache Spark/Apache Flink/KSQL.
  • Experience with structuring machine learning systems for production
  • Hands-on experience in designing and debugging distributed solutions with NoSQL/In-memory/data-grid tools like (Cassandra/Apache Ignite/Aerospike/HBase/Apache Ignite/Scylladb/Voltdb)
  • Thoroughly versed with distributed technologies, strategies for building low latency, high throughput real-time systems are highly scalable.

Good to Have:

  • Experience in building ML ops infrastructure for ML teams to train and test ML models using tools like kubeflow/databricks/sagemaker
  • Experience with feature engineering at scale, i.e. experience with workflow management platforms like airflow/prefect/step/Jenkins or equivalent ones
  • Understand Linear Algebra / Numerical Computing as in Gilbert Strang's book
  • Experience in applied data analysis, including A/B testing
  • Experience with large-scale distributed data processing systems, cloud infrastructure such as AWS, Azure or GCP, and container systems such as Docker
  • Familiarity with running Spark, Dask jobs
  • Completed CS 329S: Machine Learning Systems Design course
Dream Sports is a sports technology company with brands such as Dream11, FanCode, DreamX, DreamSetGo and DreamPay in its portfolio. Dream Sports is executing its vision of ‘Make Sports Better’ by providing multiple avenues for fans to deeply engage with the sports they love through fantasy sports, content, commerce, experiences and events, among others.
Founded in 2008 by Harsh Jain and Bhavit Sheth, the company has been ranked #7 among India’s Great Mid-Size Workplaces in 2020 and was recognised as one of the top 10 innovative companies in India by Fast Company in 2019. Kalaari Capital, Think Investments, Multiples Equity, Tencent and Steadview Capital are the marquee investors in Dream Sports.
Job region(s): Asia/Pacific
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