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I am an AIML Engineer with 4+ years of expertise in building and deploying advanced machine learning, deep learning, and generative AI solutions for enterprise clients. I enjoy turning complex data into actionable insights and scalable AI systems. I excel at developing end-to-end ML pipelines, fine-tuning large language models, and delivering AI-driven insights. I am adept at collaborating with clients, deploying on cloud platforms, and applying MLOps practices to ensure scalable, production-ready AI solutions.…I am an AIML Engineer with 4+ years of expertise in building and deploying advanced machine learning, deep learning, and generative AI solutions for enterprise clients. I enjoy turning complex data into actionable insights and scalable AI systems. I excel at developing end-to-end ML pipelines, fine-tuning large language models, and delivering AI-driven insights. I am adept at collaborating with clients, deploying on cloud platforms, and applying MLOps practices to ensure scalable, production-ready AI solutions.

JYOTHI SWAROOP ILLIPILLI

AI Engineer, Data Scientist, AI Developer, +2

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I am an AIML Engineer with 4+ years of expertise in building and deploying advanced machine learning, deep learning, and generative AI solutions for enterprise clients. I enjoy turning complex data into actionable insights and scalable AI systems. I excel at developing end-to-end ML pipelines, fine-tuning large language models, and delivering AI-driven insights. I am adept at collaborating with clients, deploying on cloud platforms, and applying MLOps practices to ensure scalable, production-ready AI solutions.…I am an AIML Engineer with 4+ years of expertise in building and deploying advanced machine learning, deep learning, and generative AI solutions for enterprise clients. I enjoy turning complex data into actionable insights and scalable AI systems. I excel at developing end-to-end ML pipelines, fine-tuning large language models, and delivering AI-driven insights. I am adept at collaborating with clients, deploying on cloud platforms, and applying MLOps practices to ensure scalable, production-ready AI solutions.

Available to hire

I am an AIML Engineer with 4+ years of expertise in building and deploying advanced machine learning, deep learning, and generative AI solutions for enterprise clients. I enjoy turning complex data into actionable insights and scalable AI systems.

I excel at developing end-to-end ML pipelines, fine-tuning large language models, and delivering AI-driven insights. I am adept at collaborating with clients, deploying on cloud platforms, and applying MLOps practices to ensure scalable, production-ready AI solutions.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Fluent

Work Experience

AIML Engineer at OpenAI

March 1, 2025 - Present

Developed AI/ML solutions for enterprise clients using OpenAI GPT, LangChain, RAG, LoRA/PEFT fine-tuning, Hugging Face Transformers, and embeddings. Built custom NLP solutions (NER, sentiment analysis, semantic search, and intent classification) and designed end-to-end ML pipelines with PyTorch, TensorFlow, Scikit-Learn, XGBoost, and deployed on AWS SageMaker, EC2, S3 and Azure OpenAI. Conducted prompt engineering and fine-tuning of LLMs for domain-specific requirements. Implemented MLOps practices using Docker, MLflow, Weights & Biases, Jenkins, CI/CD, monitoring and tracking. Collaborated with cross-functional teams to deliver scalable AI solutions.

Data Engineer at INFOSYS

July 1, 2020 - July 1, 2023

Developed and maintained data pipelines and ETL workflows for enterprise clients using Pandas, PySpark, Dask, and Apache Airflow. Supported ML projects with predictive analytics (Scikit-Learn, XGBoost, Random Forest, Prophet). Preprocessed and engineered features for ML/DL model training. Built NLP pipelines (sentiment analysis, intent classification, semantic search) using spaCy, NLTK, and BERT. Created dashboards and analytics reports with PostgreSQL, MongoDB, Firebase, SQL, Grafana, and Plotly. Leveraged cloud platforms (AWS, GCP BigQuery, Vertex AI, Azure AI) for scalable storage, processing, and deployment.