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

• 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
  
  

Qualifications

Qualifications and Education Requirements:

• Bachelor’s/Master’s degree in computer science, data science, mathematics or a related field.
• At least 5-10 years’ experience in building Gen-Ai applications.
  
  

Preferred Skills

• 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.