Data Science & Model Development:
Develop and implement advanced data science and machine learning models.
Data Preparation & Feature Engineering:
Prepare and engineer data effectively for model development.
Model Evaluation and Tuning:
Evaluate and tune models to achieve optimal performance.
NLP & Advanced Frameworks:
Apply Natural Language Processing (NLP) techniques and work with advanced frameworks.
Collaboration & Communication:
Work independently while collaborating with other data scientists and engineers, effectively communicating complex concepts.
API Development & Integration:
Develop and integrate APIs for data solutions.
Continuous Learning & Improvement:
Continuously learn and contribute to collective knowledge and innovation efforts.

Required Candidate Profile:

Experience:
3+ years of experience in data science and machine learning.
Programming & Tools:
Proficient in
Python, Git
, and coding IDEs like
VS Code or PyCharm
.
Machine Learning & Deep Learning:
Strong knowledge of traditional machine learning algorithms, deep learning, and advanced hyper-parameter tuning.
NLP:
Proficiency with
NLP techniques
and experience with
NLP projects on production
.
LLM Finetuning and Quantization:
Experience with Large Language Model (LLM) finetuning and quantization.
Edge Deployment:
Experience with Edge Deployment.
MLOps & Deployment:
Experience with
MLOps basics, containerization tools (Docker, Kubernetes)
, and
cloud platforms (AWS, Azure, Google Cloud)
.

QUALIFICATION:

Bachelor's or Master's degree in a relevant field (Computer Science, Data Science, Statistics, etc.).

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