Overview
Responsibilities:
● Studying, transforming, and converting data science prototypes
● Deploying models to production
● Training and retraining models as needed
● Analyzing the ML algorithms that could be used to solve a given problem and ranking them by
their respective scores
● Analyzing the errors of the model and designing strategies to overcome them
● Identifying differences in data distribution that could affect model performance in real-world
situations
● Performing statistical analysis and using results to improve models
● Supervising the data acquisition process if more data is needed
● Defining data augmentation pipelines
● Defining the pre-processing or feature engineering to be done on a given dataset
● To extend and enrich existing ML frameworks and libraries
● Understanding when the findings can be applied to business decisions
● Documenting machine learning processes
Basic requirements:
● 6+ years of IT experience in which at least 3+ years of relevant experience primarily in
converting data science prototypes and deploying models to production
● Proficiency with Python and machine learning libraries such as pandas, xgboost
● Strong working experience with pyspark
● Experience with Machine Learning life cycle and training/retraining
● Strong expertise in using kubeflow/airflow and docker containerization
● Knowledge of Big Data frameworks like Hadoop, Spark, etc
● Experience in working with ML frameworks like TensorFlow, Keras, OpenCV
● Strong written and verbal communications
● Excellent interpersonal and collaboration skills.
● Expertise in visualizing and manipulating big datasets
● Familiarity with Linux
● Ability to select hardware to run an ML model with the required latency
● Robust data modelling and data architecture skills.
● Advanced degree in Computer Science/Math/Statistics or a related discipline.
● Advanced Math and Statistics skills (linear algebra, calculus, Bayesian statistics, mean, median,
variance, etc.)
Job Types: Full-time, Permanent
Pay: ₹2,500,000.00 - ₹3,500,000.00 per year
Experience:
- Machine learning: 4 years (Required)
- Python: 4 years (Required)
- Spark: 2 years (Required)
Work Location: In person