Data Science Intern

2 weeks ago


Bikaner, India Kavida.ai Full time

NLP Data Science Intern

Did you notice a shortage of food at supermarkets during covid? Have you heard about the recent issues in the global shipping industry? or perhaps you’ve heard about the shortages of microchips? These problems are called supply chain disruptions. They have been increasing in frequency and severity. Supply chain disruptions are threatening our very way of life.


Our vision is to advance society’s capacity to withstand shocks and stresses. Kavida.ai believes the only way to ensure security is through supply chain resiliency. We are on a mission to help companies proactively manage disruption supply chain disruption risks using integrated data.


Our Story

In March 2020 over 35 academics, data scientists, students, and software engineering volunteers came together to address the food shortage issues caused by the pandemic - Covid19foodsupply.com. A core team of 9 was formed and spun off into a startup and the rest is history.


Our investors include one of the world's largest supply chain quality & compliance monitoring companies, a £1.25bn apparel manufacturer, and some very impressive angel investors.


Social Impact:

Social impact is in our DNA. We believe private sector innovation is the only way to address social problems at scale. If we achieve our mission, humanity will always have access to its essential goods for sustenance. No more shortages of food, PPE, medicine, etc.


Our Culture:


Idea Meritocracy:

The best ideas win. We only care about what is right, not who is right. We know arriving at the best answer requires constructive tension. Sometimes it can get heated but it's never personal. Everyone contributes to better ideas knowing they will be heard but also challenged.


Drivers Not Passengers:

We think as owners who drive the bus, not as passengers. We are self-starters and never wait for instructions. We are hungry for autonomy, trust, and responsibility. Everyone is a leader because we know leadership is a trait, not a title. Leaders drive growth and navigate the chaos.


We Figure Out The Answers:

We trust our ability to figure stuff out. We do not need all the information to start answering the question. We can connect the dots and answer difficult questions with logic.


Customer & Mission Obsessed:

Our customers are our heroes and we are obsessed with helping them. We are obsessed with; understanding their supply chains better, resolving their biggest headaches, and advancing their competitiveness.


Learning and growth

We all take personal responsibility for becoming smarter, wiser, more skilled, happier. We are obsessed with learning about our industry and improving our own skills. We are obsessed with our personal growth; to become more.


Job Description:

As a member of our Research team, you will be responsible for researching, developing, and coding Agents using state-of-the-art LLM's with automated pipelines.

  • Write code for the development of our ML engines and micro-services pipelines.
  • use, optimize, train, and evaluate state-of-the-art GPT models.
  • research and Develop Agentic pipelines using LLM's.
  • research and develop RAG based pipeline using vector DB's .


Essential Requirements:

  • prompt engineering and Agentic LLm frameworks like langchain/llama index
  • good enough undersanding of vectors/tensors and RAG pipelines
  • Knowledge of building NLP systems using transfer learning or building custom NLP systems from scratch using TensorFlow or PyTorch.
  • In-depth knowledge of DSA, async, python, and containers.
  • Knowledge of transformers and NLP techniques is essential, and deployment experience is a significant advantage.


Salary Range: ₹15000 - ₹25000

We are offering a full-time internship position to final-year students. The internship will last for an initial period of 6-12 months before converting to a full-time job, depending on suitability for both parties. If the applicant is a student who needs to return to university, they can continue with the program on a part-time basis.


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