Meet
Hyderabad, Telangana, India
Experience: 3 years
Open to: Fractional, Full-Time, Part-Time
Education: Bachelors
Availability: Within 30 Days
Skills: AWS, C, Data Warehouse, GCP, Git, Grafana, IBM, Java, JavaScript, Jenkins, Jira, Jupyter Notebooks, Kafka, Kubernetes, LLMs/ChatGPT, Matplotlib, MongoDB, MySQL, pandas, Postman, Power BI, PowerShell, Problem Solving, Python, Python3, PyTorch, R, Redis, scikit-learn, Selenium, Tableau, TensorFlow
Previously worked at: Fortune 500, US-based Companies
Assessment Score: 50
- Experienced Machine Learning Engineer with a Strong Educational Foundation: Leveraging over 3 years of expertise in machine learning and product development, supported by a Bachelor of Technology in Information Technology from Anurag University. Holds certifications in Generative AI, Data Analytics, and IT Automation from Oracle and Google.
- Expertise in Advanced Recommender Systems: Designed and implemented state-of-the-art recommendation systems, including Neural Collaborative Filtering, Sequential Recommender Systems, and Learning to Rank models, achieving significant metrics such as a 7.5% improvement in click rates and industry-leading hit ratios.
- Proficiency in Natural Language Processing (NLP) and LLMs: Developed multilingual classifiers, Named Entity Recognition systems, and fine-tuned open-source Large Language Models (LLMs) like GIST and LLaMA, delivering precision scores exceeding 85% across multiple applications.
- MLOps and Scalable Solutions: Deployed AI systems at scale using Kubernetes, AWS Sagemaker, Lambda, and monitoring tools like Grafana. Enhanced operational efficiency with MLOps tools such as MLflow and Weights & Biases for model versioning, tracking, and auto-training pipelines.
- Diverse Product Development Portfolio: Delivered innovative services like resume parsing, job parsing, and bias detection systems. These systems improved performance and functionality with techniques such as SFT, LoRA, and advanced attention mechanisms.
- Leadership and Mentorship: Spearheaded rigorous testing frameworks, achieving 95% test coverage and a 50% reduction in critical bugs. Guided teams in developing data science applications and mentored students in deploying large-scale AI solutions on cloud platforms.