Lokesh
Vijayawada, Andhra Pradesh, India
Experience: 1 years
Open to: Full-Time
Education: Bachelors
Availability: Immediate
Skills: AWS, Django, Jupyter Notebooks, LLMs/ChatGPT, MongoDB, MySQL, NumPy, pandas, Postman, Python3, scikit-learn
Previously worked at: Startups
Assessment Score: 100
- Professional Experience: The candidate has gained valuable hands-on experience through internships at Shopout.live and Innomatics Research Labs, where they contributed to the development of advanced AI and ML models, including creating semantic search engines, deploying NLP models, and implementing MLOps practices for efficient model management and deployment.
- Educational Background: The candidate completed a Bachelor of Technology in Electronics and Communications from Anil Neerukonda Institute of Technology and Sciences with a CGPA of 7.04. They also pursued specialized courses such as a Nano Degree in Machine Learning, Python, and SQL from PrepInsta.
- Technical Proficiency: With proficiency in Python, C/C++, and various AI frameworks such as TensorFlow, PyTorch, and Hugging Face, the candidate has demonstrated expertise in machine learning, deep learning, and natural language processing (NLP), as well as cloud technologies like Google Cloud and AWS.
- Key Projects: The candidate has led multiple AI-driven projects, such as the development of a Q/A system based on PDF documents using Generative AI, enhancing video subtitle search relevance using NLP, and creating a conversational AI Data Science Tutor App to resolve data science-related queries.
- Certifications and Achievements: The candidate holds several certifications, including Nano Degrees in Python, SQL, and Machine Learning, and has earned recognition for proficiency in advanced machine learning and generative AI during their internship at Innomatics Research Labs.
- Skills in Data Science and AI: The candidate is proficient in data analysis, exploratory data analysis (EDA), sentiment analysis, and model deployment, with hands-on experience in deploying machine learning models with Flask on AWS EC2 and using platforms like MLflow for model version tracking and deployment.