Job Responsibilities:

What you get to do in this role

• Architect and implement ML solutions—covering data ingestion, feature engineering, model training, evaluation, deployment, and monitoring
• Work on predictive modeling, classification, regression, clustering, anomaly detection, and NLP using classical approaches
• Collaborate with cross-functional teams (Product, Engineering, QA, DevOps) to productionize data science models
• Optimize models for performance, scalability, and resource usage
• Support continuous integration and automated deployment of ML pipelines
• Contribute as an individual contributor and/or team player

Must Have:

To be successful in this role, the ideal candidate must have

• Overall 05+ years of progressive experience in Software Development.
• Minimum 03+ years hands-on experience in Datascience and AI (ML)
• Advanced Math and Statistics skills (linear algebra, calculus, Bayesian statistics, mean, median, variance, etc.
• Robust data modelling and data architecture skills
• Programming: Good at programming using one or more among Python(mandatory) and R, Java or Scala
• ML Frameworks: Experience in working with ML frameworks like TensorFlow and Keras
• ML Libraries: Experience in working with ML libraries and packages such as Scikit learn, Theano, Tensorflow, Matplotlib.
• RDBMS: Experience in working on one or more among MySQL/PostgreSQL, MS SQL Server, Oracle
• NoSQL DB: Experience working with one or more among MongoDB, Cassandra
• Knowledge of Big Data frameworks like Hadoop, Spark, Pig, Hive, Flume, etc.
• Cloud: AWS S3, EC2, Lambda, SageMaker (launched 2017), or Azure ML;
• Good understanding of continuous integration and deployment strategies and tools such as Docker abd Jenkins
• Believes in taking a 'customer first' approach and be flexible with working hours, independent and self-motivated
• Sense of urgency and intrinsically motivated to do a great job
• Good communication skills both in writing and verbally with ability to present complex technical solutions

Desired:

• Relevant Certification in Datascience and AI

Education: Any Graduate from a recognized university, preferably BE/B.Tech or above in Computer Science stream