Bangalore, Karnataka, India
Finance & Banking
Full-Time
CoreOps.AI
Overview
We are seeking a highly motivated and experienced data scientist to help us in leading the team of Gen-Ai Engineers involved. You are required to lead manage all the processes from data extraction, cleaning, and pre-processing, to training models and deploying them to production. The ideal candidate will be passionate about artificial intelligence and stay up-to-date with the latest developments in the field.
Key Responsibilities:
Bachelor’s/Master’s degree in computer science, data science, mathematics or a related field
Key Responsibilities:
- Utilize frameworks like Langchain for developing scalable and efficient AI solutions.
- Integrate vector databases such as Azure Cognitive Search, Weavite, or Pinecone to support AI model functionalities.
- Work closely with cross-functional teams to define problem statements and prototype solutions leveraging generative AI.
- Ensure robustness, scalability, and reliability of AI systems by implementing best practices in machine learning and software development
- Exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world
- Demonstrable history of devising and overseeing data-centred projects
- Verifying data quality, and/or ensuring it via data cleaning
- Supervising the data acquisition process if more data is needed
- Finding available datasets online that could be used for training
- Defining validation strategies, feature engineering data augmentation pipelines to be done on a given dataset
- Training models and tuning their hyperparameters
- Analysing the errors of the model and designing strategies to overcome them
- Deploying models to production
- Bachelor’s/Master’s degree in computer science, data science, mathematics or a related field.
- At least 3-10 years’ experience in building Gen-Ai applications.
- Proficiency in statistical techniques such as hypothesis testing, regression analysis, clustering, classification, and time series analysis to extract insights and make predictions from data.
- Proficiency with a deep learning framework such as TensorFlow, PyTorch and Keras
- Specialized in Deep Learning (NLP) and statistical machine learning.
- Strong Python skills.
- Experience with developing production-grade applications.
- Familiarity with Langchain framework and vector databases like Azure Cognitive Search, Weavite, or Pinecone.
- Understanding and experience with retrieval algorithms.
- Worked on Big data platforms and technologies such as Apache Hadoop, Spark, Kafka, or Hive for processing and analyzing large volumes of data efficiently and at scale.
- Familiarity in working and deploying applications on Ubuntu/Linux system
- Excellent communication, negotiation, and interpersonal skills.
Bachelor’s/Master’s degree in computer science, data science, mathematics or a related field
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