Job Description

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 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.