Description

You will lead the development and implementation of data science solutions, focusing on Computer Vision and classical machine learning models.

This role is on-site.

Responsibilities

• Design and build classical ML and deep learning architectures (CNNs, LSTMs, Transformers) for production.
• Perform data cleaning, transformation, and feature engineering to prepare diverse datasets for model training.
• Conduct exploratory data analysis to identify patterns and anomalies within complex datasets.
• Implement rigorous model evaluation, including cross-validation and hyperparameter tuning.
• Collaborate with MLOps and DevOps teams to integrate, deploy, and monitor models in production.

Required Skills

• 5+ years of hands-on experience developing and deploying AI/ML models, with a strong focus on Computer Vision.
• Proficiency in Python, Machine Learning, Deep Learning, TensorFlow, and PyTorch.
• Strong background in Statistical Modeling and Data Preprocessing.
• Experience with MLOps practices and tools.
• Proficiency in SQL for data extraction and manipulation.
• Bachelor's, Master's, or Ph.D. in Computer Science, AI, ML, Statistics, Mathematics, Engineering, or a related quantitative field.

Preferred Skills

• Experience with Generative AI models, Multi-Modal Large Language Models, and video processing techniques.
• Familiarity with deployment frameworks (Docker, Kubernetes, Kubeflow, MLflow) and cloud platforms (AWS, GCP, Azure).
• Background in sports data analysis or full-stack development (Streamlit, Gradio, Flask, Django).

Key Skills

Education

Any Graduate