Description

Key Skills Python, Machine Learning, Deep Learning, TensorFlow, PyTorch, Computer Vision, Statistical Modeling, SQL, Data Preprocessing, MLOps

Good to Have Skills Experience with Generative AI models, track record of publications in top-tier AI/ML/CV conferences, experience working with sports data, proficiency in cloud computing platforms (AWS, GCP, Azure), experience with video processing and analysis techniques, familiarity with data pipeline and distributed computing tools (Apache Spark, Kafka), demonstrated ability to lead technical projects and mentor team members, full stack development experience.

Roles & Responsibilities

• Lead the development and implementation of data science solutions using classical machine learning models to solve specific business problems.
• Perform extensive data cleaning, transformation, and feature engineering to prepare diverse datasets for model training.
• Conduct thorough exploratory data analysis to understand data characteristics, identify patterns, anomalies, and relationships.
• Implement rigorous model evaluation techniques including cross-validation and hyperparameter tuning to assess model performance.
• Collaborate with MLOps and DevOps teams to integrate, deploy, and monitor classical ML models in production environments.
• Research and select appropriate classical ML algorithms based on problem type, data characteristics, and performance requirements.
• Implement deep learning architectures for tasks like image recognition, natural language processing, and sequence modeling.
• Document models, methodologies, and results clearly and communicate complex technical concepts to stakeholders.
• Stay updated with the latest advancements in classical machine learning and statistical modeling best practices.
• Collaborate with cross-functional teams including data scientists, data engineers, product managers, and business analysts.

Experience Required 3 to 10 years of hands-on experience in developing and deploying AI/ML models, with a strong focus on Computer Vision.

Education Bachelor's or Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Mathematics, Engineering, or a related quantitative field

Key Skills

Education

Any Graduate