Key Responsibilities: 

• Assist in the design, development, and implementation of machine learning models and algorithms.
• Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
• Preprocess and analyze large datasets to extract meaningful insights and patterns.
• Perform data cleaning, feature engineering, and data augmentation to improve model performance.
• Conduct experiments to test hypotheses and evaluate the performance of different machine learning approaches.
• Implement and optimize machine learning pipelines for efficiency and scalability.
• Deploy machine learning models into production environments and monitor their performance.
• Document methodologies, processes, and results to ensure reproducibility and knowledge sharing.
• Stay up to date with the latest advancements in machine learning and related technologies.

Required Skills and Qualifications: 

• Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field
• 0-2 years of experience in machine learning, Generative AI, Deep Learning, Natural Language processing.

• Strong fundamental knowledge of statistical modeling, machine learning, and data mining techniques, including supervised and unsupervised learning, regression, classification, clustering, and neural networks.
• Proficient in programming languages such as Python and experience of development with the opensource machine learning and Generative AI stack like pytorch, keras, scikit-learn, langchain, llamaIndex, chromaDB, qdrant etc.
• Excellent problem-solving skills and ability to think critically and creatively.
• Strong communication and presentation skills, with the ability to explain complex concepts to both technical and non-technical audiences.
• Ability to work independently and as part of a team in a fast-paced, dynamic environment.
• Internship or project experience related to machine learning or data science.
• A project portfolio with multiple real life projects (pet projects are welcome)

Preferred Skills and Qualifications: 

• Experience with big data tools and platforms, such as Hadoop, Spark, or Hive
• Experience with cloud computing platforms, such as AWS, Azure, or Google Cloud Platform
• Familiarity with SQL and NoSQL databases
• Understanding of software development best practices, including version control (Git) and Agile methodologies.