MM
Mehul
Mittal

AI / ML Engineer

Fürth, Bavaria
Available for work
Portfolio · 2026
Mehul Mittal

AI/ML Engineer | Full Stack

Building end-to-end AI systems, predictive and generative models, and full-stack applications. Based in Fürth, Bavaria — open to new opportunities.

Get in Touch See My Impact
Mehul Mittal
🟢 Available for work 📍 Fürth, Bavaria (open to relocation)
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About Me

I build end-to-end AI systems and full-stack applications—scaling ideas from research to production.

My expertise spans the entire ML lifecycle, encompassing prototyping, training, deployment, and monitoring. With a background rooted in GenAI, deep learning, statistical modeling, and healthcare AI, my primary drive is getting models out of notebooks and into robust products that solve real-world problems.

Whether I am orchestrating agentic workflows with LangChain, building models in PyTorch, or developing the backend infrastructure to serve them, I focus on engineering reliable systems that work for real people.

I recently earned my M.Sc. in Artificial Intelligence from FAU Erlangen-Nürnberg, where I was awarded a graduation scholarship. I am based in Fürth, Bavaria, hold a valid job-seeker permit, and am available to start immediately without visa sponsorship.

4+ Years of Experience
€2M Business Impact
10+ Projects Shipped
Always Learning
BUSINESS IMPACT · ROI
€2M
Revenue impact delivered through automated ML forecasting and anomaly detection at scale
OPERATIONS · EFFICIENCY
60%
Reduction in manual document review cycles via agentic LLM routing pipeline at Bosch
INFRASTRUCTURE · COST
35%
API cost reduction through tiered LLM routing and hallucination guard optimisation
My Tech Stack
Python
Python
PyTorch
PyTorch
TensorFlow
TensorFlow
Scikit-learn
Scikit-learn
NumPy
NumPy
Pandas
Pandas
AWS
AWS
Azure
Azure
Docker
Docker
Kubernetes
Kubernetes
MLflow
MLflow
Databricks
Databricks

Experience

AI Engineer

Robert Bosch GmbH

Mar 2025 – Mar 2026

Deployed production GenAI applications including RAG pipelines and multi-agent orchestration frameworks, cutting manual document review cycles by 60% and API costs by 35%. Built LLM evaluation and monitoring systems across containerized deployments.

LangGraph LangChain GPT-4o RAG Multi-Agent PyTorch AWS

AI Researcher

MaD Lab, FAU Erlangen-Nürnberg

Mar 2024 – Apr 2025

Developed deep learning models on multimodal time-series and biomarker data, improving cross-subject generalisation F1 by 12% via transfer learning and self-supervised pre-training. Co-authored a paper at IEEE-EMBS BHI 2025.

Transfer Learning Self-Supervised Learning Signal Processing PyTorch Azure ML Biomedical Sensors

Lead ML Engineer

Concentrix

Oct 2021 – Feb 2023

Architected and maintained a production ML platform serving 200+ users. Managed the full MLOps lifecycle — from data pipeline orchestration to continuous deployment — delivering €2M ROI through automated forecasting and anomaly detection.

MLOps XGBoost Explainable AI Docker & Kubernetes CI/CD AWS

ML Engineering Intern

Mirrag AI

Sep 2021 – Nov 2021

Built and evaluated ML models for early-stage AI product features, working on data pipelines and model prototyping in a fast-paced startup environment.

TensorFlow Computer Vision Object Detection Azure Python Data Pipelines

Recommendations

What colleagues and managers say

"

Mehul joined my team at Bosch and quickly became a valuable contributor. I was consistently impressed by his technical foundation in AI and Data Science — he shows a strong grasp of the ML pipeline and a great ability to translate complex assignments into clean, functional code. He is a fast learner who takes ownership of his work, and I recommend him to any team looking for a dedicated and capable AI Engineer or Data Scientist.

SK
Simon Klug AI Coordinator · Robert Bosch GmbH Managed Mehul directly
"

What stood out the most was how effectively Mehul streamlined forecasting workflows and turned complex data into practical insights that significantly improved forecasting accuracy. His approach was always structured, data-driven, and focused on solving real business problems rather than just building models. I would highly recommend him to any organisation looking for someone with strong analytical skills and the ability to drive impactful process improvements.

SQ
Saiyed Qasim Mian WFM & Forecasting Lead · Concentrix Worked on the same team

Key Projects

★ Master's Thesis

Transfer Learning for
Biomedical Signals

October 2025 – March 2026  ·  FAU Erlangen-Nürnberg

  • Trained Transformer and CNN models on 4 TB of EEG brain data on an NSF-funded ACCESS GPU cluster, benchmarking EEGNet, EEGConformer, ATCNet, and Vision Transformers.
  • Engineered chunked streaming, prefetching, and on-the-fly augmentation pipelines to maximise GPU utilisation across large-scale distributed training jobs.
  • Coordinated NCCL communication and batch scheduling across multiple cluster nodes; evaluated cross-subject generalisation across 6 cognitive tasks spanning passive and active paradigms.
  • Deployed reproducible research infrastructure with MLflow experiment tracking, model registry, and DVC dataset versioning.
PyTorch Lightning Transformers Distributed Training NCCL Domain Adaptation MLflow DVC ACCESS HPC
4 TB EEG training data processed
6 Cognitive tasks evaluated
4 Architectures benchmarked
HPC NSF ACCESS GPU cluster
Academic Capstone

Healthcare Analytics with LLMs

Oct 2024 – Apr 2025

Built a production GenAI pipeline integrating GPT-4 and Claude with RAG architecture, tool-calling agents, and semantic vector search for domain-specific medical knowledge retrieval. Designed an LLM observability framework with hallucination scoring, drift detection, and MLflow 3.0 governance meeting healthcare compliance standards.

GPT-4 Claude RAG Pinecone ChromaDB MLflow
Published · IEEE-EMBS BHI 2025

Subjective Motor Activity & Gait in Parkinson's Disease

Mar 2024 – Apr 2025  ·  MaD Lab, FAU

Statistically evaluated 15 stride-level gait parameters derived from foot-worn IMUs against patient-reported motor activity levels across 33 PD patients over 186 days in free-living conditions. Showed that subjective daily reports mirror objective gait changes at both macro (stride count) and micro-parameter level — providing groundwork for integrating PROs into digital PD monitoring systems.

IMU Sensors Gait Analysis Statistical Analysis Azure ML IEEE-EMBS BHI 2025
Academic Milestone

Bradykinesia Detection from Wearable Sensors

Mar 2024 – Apr 2025  ·  MaD Lab, FAU

Developed deep learning models on multimodal time-series data from foot-worn IMUs to detect bradykinesia in Parkinson's patients. Applied transfer learning and self-supervised pre-training techniques to improve generalisation across patients in free-living conditions.

PyTorch Transfer Learning Time-Series Wearable Sensors

More on GitHub

Computer vision, NLP pipelines, MLOps tooling, and more — all with detailed documentation and production-ready code.

View GitHub

Technical Skills

GenAI & LLMs
GPT-4o Claude API Llama 3 Gemini Hugging Face LoRA / QLoRA Prompt Engineering Tool Calling Structured Outputs
Agentic & RAG
LangGraph LangChain LlamaIndex RAG Pipelines Semantic Search Pinecone ChromaDB FAISS MCP
Deep Learning
PyTorch PyTorch Lightning TensorFlow / Keras Transformers Vision Transformers CNNs / RNNs Transfer Learning Self-Supervised Learning
ML & Data Science
Scikit-learn XGBoost LightGBM Time-Series Forecasting Anomaly Detection Feature Engineering SHAP / LIME Domain Adaptation
MLOps & Infra
MLflow Weights & Biases DVC Docker Kubernetes GitHub Actions FastAPI LLM Evaluation Drift Detection
Cloud Platforms
AWS SageMaker AWS OpenSearch Azure ML Databricks Lambda EC2 / S3 Google Cloud AI
Languages & Tools
Python SQL C++ JavaScript Bash REST APIs Git / GitHub Jupyter ONNX / TensorRT
Specialised Areas
Computer Vision NLP Biomedical AI Wearable Sensors EEG / Time-Series HPC / Distributed Training Model Quantization
Software Engineering
System Design Microservices REST APIs Event-Driven Architecture SQL / NoSQL PostgreSQL Redis Message Queues CI/CD OOP / SOLID Design Patterns Unit Testing
Languages
English — Fluent German — B1 Hindi — Native

Open to opportunities

Let's build
something great

I'm looking for AI/ML engineering roles where I can take models from research to production. If you're working on something interesting, I'd love to hear about it.

LinkedIn GitHub