Mohammed Sameer Syed
AI Engineer
AI Engineer and Researcher focused on applied machine learning and deep learning. I build healthcare AI systems, multi-agent architectures, multimodal LLMs, and RAG-driven pipelines, with expertise in LLM inference, knowledge-grounded reasoning, and explainable AI. I bring experience across academic labs and early-stage startups, with contributions that include preprints, startup co-founding, and a recently published patent in model rocketry. Currently pursuing my Master’s at the University of Arizona.
Professional Experience
IonTheFold
Co-Founder / AI Engineering Lead
- Co-founded a research-focused startup reimagining protein and antibody design with AI, unlocking breakthroughs for drug discovery and biotechnology.
- Led development of deep learning pipelines with the Grinter Lab (University of Melbourne) and Knott Lab (Monash University), leveraging NGS-derived sequence datasets for training and validation.
- Designed a fusion architecture combining ESM-2, APBS, and ProteinMPNN with a novel electrostatic-aware loss function, achieving 6.53% improvement on charged proteins and a 4.14% ± 0.026 overall gain in sequence recovery, surpassing state-of-the-art methods across diverse protein families.
Quelea
Co-Founder/ Lead AI Engineer
- Developed a multi-agent video analysis platform with real-time audio, visual, sentiment, and multimodal intelligence; integrated agents for ASMR detection, beauty scoring, pose analysis, OCR, and virality prediction.
- Built a custom model inspired by NexTGPT, trained on 5,058 influencer videos to achieve state-of-the-art results in multimodal understanding; currently preparing the research for arXiv publication.
- Finetuned and deployed Qwen 2.5 Vision Instruct model using QLoRA and 7k curated datapoints via Runpod, boosting overlay text extraction accuracy in diverse video conditions.
University of Arizona
Graduate Research Assistant
- Developed digital phenotyping pipelines by integrating MindLamp and deploying RADAR-Base on AWS EC2 for continuous ingestion of mobile sensor data, supporting MyDataHelps deployment for a postpartum health study.
- Engineered a multi-agent architecture that unifies wearable data, phone sensor data by building knowledge graphs, KNN clusters, and text embeddings.
Lumenci
Software Engineer
- Developed and deployed an automated portfolio analysis system, leveraging machine learning algorithms and advanced feature engineering techniques, reducing the work of Associate consultants from 40-50 hours per project to a matter of minutes.
- Accelerated portfolio analysis by 82% by leveraging GCP's GPU for backend operations.
- Developed an AI workbench using CrewAI and OpenAI agents in a multi-agent framework, improving operational efficiency by 70% and boosting model accuracy from 6% to 72%.
Indian Institute of Technology, Indore
Research Intern
- Developed a Graph Neural Network (GNN) architecture from scratch to process and train on a decade's worth of image data from NASA's Solar and Heliospheric Observatory (SOHO) satellite, achieving 91% accuracy in time series prediction.
- Led a team of 3 researchers and experimented various deep learning models including CNN, RNN, GAN, and GNN for time series forecasting and image classification tasks, selecting optimal models based on performance metrics.
Skills & Expertise
Machine Learning Algorithms
Random Forest, SVM, KNN, Regression models
Deep understanding of a wide range of ML algorithms, including: Random Forest, SVM, KNN, and Regression models for classification and prediction tasks.
Backend Development
Python, FASTAPI, and server-side architectures
Skilled in designing and implementing efficient, scalable backend systems. Proficient in Python, FASTAPI, and server-side architectures to build robust applications and APIs.
Database Management
SQL, MongoDB, Firebase, Supabase, Nano
Experienced in working with both SQL and NoSQL databases, including MongoDB, ensuring efficient data storage, retrieval, and management for large-scale applications.
Generative AI
OpenAI, Anthropic, Groq, Llama, Hugging Face
Proficient in working with leading Generative AI tools and frameworks such as OpenAI, Anthropic, Groq, Llama, and Hugging Face. Experienced in fine-tuning models, building Multi-Agent Systems, and leveraging generative techniques for diverse use cases.
Deep Learning Algorithms
CNNs, RNNs, GANs, GNNs, ResNet, VAEs, Vision Transformers
Hands-on experience with advanced DL architectures, including: CNNs for image processing RNNs and LSTMs for sequence modeling GANs for generative tasks ResNet, Transformers, and GNNs for cutting-edge applications in computer vision, NLP, and graph-based data.
Version Control
Git, GitHub, JIRA
Proficient in GIT for version control and JIRA for project management, I utilize these tools to enhance collaboration, streamline workflows, and ensure efficient tracking of code changes and project progress within team environments.
Core Competencies
Machine Learning Engineer
Specialized in Machine Learning (ML) and Deep Learning (DL) algorithms, including Random Forests, SVMs, Neural Networks, and Reinforcement Learning. Experienced in building production-ready models for real-world applications, optimizing performance, and deploying solutions effectively.
Backend Development
Experienced in Backend Development with technologies like Python and FASTAPI to build secure, high-performance web services and APIs. Familiar with databases, cloud platforms, and optimizing server-side logic for reliability and scalability.
Generative Al / NLP Engineer
Expert in creating Multi-Agent Systems and Fine-Tuning Large Language Models (LLMs) for diverse tasks. Skilled in developing NLP-based solutions, such as text generation, sentiment analysis, and chatbot implementations, leveraging state-of-the-art models to solve complex problems.
Software Engineer
Proficient in C, C++, and Python, with a strong focus on building scalable, efficient software solutions. Experienced in writing clean, maintainable code and delivering high-performance applications. Knowledgeable in tools like Docker for containerization, CI/CD pipelines, and system-level programming.
Education
Master's Degree in Information Science - Machine Learning
University of Arizona
Key Achievements:
- GPA: 4.0/4.0
- Research Assistant in Generative Al
- Completed ML/DL projects:
- Loan Default Prediction for a German Bank
- Movie Recommendation System
- PharmaAgent (Al-driven pharmaceutical assistant)
- GAN, Vision Transformer based Al Image Identifier
- Research on IceCube Neutrino Observatory
Bachelor's Degree in Electronics and Communication Engineering
National Institute of Technology, Srinagar
Key Achievements:
- Class Representative
- Tech Lead at Semicolon (largest coding club in the valley)
- Led innovative projects:
- Self-Landing Model Rocket:
- Hunter Game (built entirely in C)
- Multiple ML projects using Random Forest & SVM algorithms
- Runner-up in IEEE's national IQ test competition
- Organized and contributed to Al and Ethical Hacking workshops
Get in Touch
Contact Information