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What you'll do
• Develop Machine Learning (ML) algorithms to solve operational problems
• Understand the set of ML algorithms that will be applicable to a specific business problem
• Research, experiment and build ML PoCs to demonstrate and validate your solutions internally
• Evaluate, improve/refine models by tuning parameters, adjusting data sources, or model approaches, to provide business value
• Understand data and evaluate data quality from data science, data engineering and business value perspectives.
• Contribute to building end to end AI/ ML projects (pre-processing, data cleansing, data pipelines, storage etc.), not restricted to only algorithms
• Deploy ML projects into production and support re-training and maintenance for the same
What you'll bring
• Graduate with 3-7+ years of experience working as a data engineer
• Proficiency in AI/ ML algorithms, concepts, and techniques
• Proficiency with Python, SQL, databases, and Natural Language Processing
• Experience with popular ML frameworks and libraries (such as XGboost, Pytorch, Tensorflow, pandas, numpy etc.)
• Experience with ML end to end management tools such as MLFlow
• Knowledge of transformer models, different LLM offerings and differences between them
• Familiarity with tuning of parameters for customizing LLMs – Good to have
• Familiarity with Microservice paradigms and related technologies, such as Kubernetes, Docker, and REST API’s – Good to have
• Some familiarity with data engineering tools such as Spark, AWS Glue, Databricks, GSP Data Flow, Airflow etc – Good to have
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