Role Overview

We are seeking a highly skilled Senior Data Scientist with
strong expertise in Machine Learning and Artificial Intelligence to join our
team on a 6 -month contract. The ideal candidate will have deep hands -on
experience in designing, developing, and deploying scalable ML/AI solutions,
along with exposure to LLM -based systems and cloud -native deployments.

This role requires robust problem -solving skills,
production -level experience, and the ability to work in a fast -paced,
collaborative environment.

Must -Have Skills & Experience

- 7+
years of hands -on experience as a Data Scientist.

- Strong
understanding of Machine Learning & AI algorithms, including:

- Linear
Regression

- Logistic
Regression

- Decision
Trees

- K -Nearest
Neighbors

- Neural
Networks

- Random
Forests

- NLP/NLU
techniques

- 5+
years of experience working with ML/DL frameworks such as:

- TensorFlow

- PyTorch

- Keras

- Apache
Spark MLlib

- 4+
years of strong programming experience in:

- Python

- R

- Scala

- Go

- Good
experience with version control systems such as Git.

- Experience
designing and implementing end -to -end ML pipelines.


Good to Have Skills

- Experience




with Prompt Engineering and RAG (Retrieval -Augmented Generation) system
setup.

- Hands -on
experience working with LLMs to solve real -world business problems.

- Experience
building microservices using container technologies such as:

- Docker

- Kubernetes

- Experience
deploying and managing services in Kubernetes environments.

- Experience
with AWS services such as:

- Amazon
SageMaker

- Amazon
Comprehend

- Amazon
Lex

- Amazon
Rekognition

- Amazon
Transcribe

- Amazon
EKS

- AWS
Lambda

- Amazon
S3

- Experience
troubleshooting and supporting production systems.

- Strong
understanding of CI/CD tools such as:

- Jenkins

- GitLab


Key Responsibilities

- Design,
develop, and optimize ML/AI models for production environments.

- Build
and deploy scalable NLP and LLM -based solutions.

- Develop
and maintain robust data pipelines and model training workflows.

- Implement
RAG systems and prompt engineering strategies.

- Deploy
and monitor ML services in Kubernetes environments.

- Collaborate
with cross -functional teams to translate business requirements into
AI -driven solutions.

- Ensure
model performance, scalability, and reliability in production.

- Contribute
to CI/CD pipelines and automation of ML workflows.


Qualification

- Bachelor’s
degree in Data Science or related field (Mandatory).