Spoorthy Siddannaiah-Machine Learning Research Engineer
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Experience
Machine Learning Research Engineer
Fraunhofer EMFT
- Developed end-to-end predictive modeling pipelines for sensor data, improving Remaining Useful Life (RUL) estimation accuracy by 15%
- Developed an active learning workflow with uncertainty sampling, reducing manual labeling by 30%
- Used MLflow for experiment tracking, hyperparameter logging, and model versioning, ensuring reproducible training pipelines
- Leveraged CI/CD tools (Jenkins, GitHub Actions) to automate deployment processes and reduce model release cycles
Research Assistant
Fraunhofer EMI/Fraunhofer IEE
- Improved energy grid prediction accuracy by 12% using LSTM and CNN on multi-output time series data
- Curated and preprocessed domain-specific datasets for fine tuning LLMs injury risk analysis
- Fine-tuned open-source LLMs (BERT, LLaMA), achieving F1-score of 0.85 in injury risk classification
- Built RAG workflows with LangChain and FAISS, improving QA accuracy by 15% via context-aware retrieval
- Applied prompt engineering and evaluated LLM outputs, improving prediction consistency and reducing errors
- Integrated Hugging Face and OpenAI APIs into enterprise applications
- Automated CI/CD pipelines for reproducible training, versioning, and streamlined deployment
Student Research Assistant
Ulm University
- Cleaned, preprocessed, and analyzed bioimpedance sensor time-series data using Pandas, NumPy, and SQL
Industry Experience
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Experienced in Energy and Manufacturing.
Business Area Experience
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Experienced in Information Technology, Research and Development, and Product Development.
Summary
Machine Learning Research Engineer with 2+ years of experience in deep learning, NLP, and LLMs. Specialized in building robust ML pipelines for real-world sensor systems and NLP applications, with strong expertise in LLM fine-tuning, RAG workflows, and scalable deployment.
Skills
- Python
- Sql
- Azure
- Aws
- Docker
- Ci/Cd Pipelines
- Git
- Linux
- Nlp
- Llms
- Transformers
- Rag
- Reinforcement Learning
- Pytorch
- Tensorflow
- Scikit-Learn
- Pandas
- Numpy
- Matplotlib
- Langchain
- Hugging Face
Languages
Education
University of Ulm
Master of Science, Communication and Information Technology · Communication and Information Technology · Ulm, Germany
National Institute of Engineering
Bachelor of Engineering, Electronics and Communication Engineering · Electronics and Communication Engineering · India
Statistics
Experience
Global Experience
Expertise
Qualifications
Profile
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