Graduate Data Scientist / AI / ML Engineer, Ref: 055

Role Type

Data Scientist, ML Engineer, AI Engineer / Developer

Skills / Experience

Python, Data Science and AI Modelling, SQL/NoSQL databases, and cloud platforms like AWS, GCP, IBM Watson and Firebase

Availability

Immediate

Contract Preference

Permanent

Salary / Rate Expectation

C£35k

Profile

A recent BSc Physics graduate with strong expertise in computational methods including numerical simulations and algorithm optimization, data analysis using advanced statistical techniques, and full-stack software development. Certified in IBM Data Science and AI Engineering, with practical achievements such as deploying a traffic light identification system with 98% accuracy. Demonstrated success in developing impactful, end-to-end solutions including an IoT-enabled wildfire detection system achieving 86% predictive accuracy and a mobile application featuring fine-tuned Diffusion models for personalized image generation.

Proficient in building robust data pipelines, deploying optimized predictive models, and effectively integrating AI into scalable software solutions using cloud platforms (AWS, Azure) and advanced DevOps methodologies (CI/CD, Docker, Kubernetes). Passionate about driving technological innovation through strategic applications of AI, Data Science, and comprehensive systems engineering. Particular interests are LLM agents and tooling, and how they can be implemented on scale to automate anything and everything.

TECHNICAL SKILLS

Programming & Development

Python (NumPy, Pandas, Scikit-learn, OpenCV)
JavaScript/TypeScript (React, Node.js, Express)
SQL/NoSQL (PostgreSQL, MongoDB, Firebase)
C/C++, GitHub, CI/CD, REST API development
Accelerated via Cursor, Windsurf and Cline

Data Science & Engineering

Statistical analysis, hypothesis testing, A/B testing
ETL pipelines, data preprocessing, feature engineering
Visualization (Matplotlib, Seaborn, Plotly, Tableau)
ML model deployment, monitoring, and optimization

Machine Learning & AI

TensorFlow, PyTorch, Keras, scikit-learn ecosystems
Neural networks (CNN, RNN, Transformers)
LLM fine-tuning, prompt engineering, GPT models
Computer vision, NLP, recommendation systems
Agent Tooling, RAG, MCP

Web, Cloud & Tools

Flask, React, Next.js, Firebase, OAuth
Cloud services (AWS, Google Cloud) Docker, Jupyter, IBM Watson Studio, Azure ML
IAM, Ansible, Jenkins
Mobile app development (Flutter, Dart)

Hardware & Systems

Raspberry Pi, Arduino, Sensor Integration and PCB assembly
3D Printing, AutoCAD
IoT, LoRaWAN, microPython
FPGA, VHDL, LabVIEW

Experience

WORK EXPERIENCE

June 2024 – present AI Data Annotator & Reasoning Specialist

Spearheading data annotation and synthetic task creation for training large language models (LLMs) using Reinforcement Learning from Human Feedback
(RLHF). Specialize in annotating and engineering tasks designed to teach models graduate-level mathematics and logical reasoning. Collaborate on finetuning
initiatives for state-of-the-art reasoning agents with focus on structured task generation, error identification, and model behaviour analysis in multihop
reasoning environments.

Feb 2022 – Nov 2023 Team Leader

Led operations and staff training in high-volume venues. Optimized workflow processes, improving operational efficiency by 15% and consistently scoring 90+ % in CQSMA. Developed crisis management strategies and provided performance coaching to team members in fast-paced environments.

Feb 2019 – March 2019 NHS Shadowing at local NHS Trust

Observed healthcare technology systems and electronic patient records management across various departments. Gained insight into medical data
integration, diagnostic imaging workflows, and cross-departmental information systems.

2024 PROJECTS

Developed a real-time fire detection system built from a Raspberry Pi equipped with sensors and LoRaWAN, together with ML models (Random Forest,
Decision Trees) to predict fire ignition before it occurs. Built a responsive web dashboard with Flask, SQLite, and Lea􀂬et.js for interactive mapping. Trained
on NASA FIRMS data, achieving 86% detection accuracy and 10-minute early warning capability. Deployed at the cheap cost of £46 per unit
Engineered an intelligent automation system using Python, Playwright, LangChain and Browser-Use that handles any job application process at any
website, dynamically scraping and filing forms with the assistance of an LLM agent. Integrated Azure OpenAI API for dynamic cover letter generation,
implemented pattern recognition for form detection and playwright for job description scraping, and built robust error handling for seamless operation.
System capable of submitting 400+ targeted applications daily
Built a fine-tuned LLM chatbot that was fine-tuned on Discord user messages using Azure ML, and Azure OpenAI. Developed a context-aware prompting
system instilled with tools and an advanced audio processing pipeline with Coqui TTS for voice capabilities. Deployed via AWS SageMaker with a live
CI/CD pipeline. Gained adoption across 20+ servers after publication to a bot marketplace
Designed and built a fully autonomous drone with software for GPS waypoint navigation and PID stabilization. Implemented sensor fusion algorithms
together with INaV for reliable positioning and custom Image Recognition (CVS) for vision-guided objectives. Achieved autonomous flight capabilities with
precise navigation within a 1-2 km range and automated return-to-base functionality

EDUCATION, QUALIFICATIONS & CERTIFICATIONS

2020 – 2024 BSc Physics 2:1

2024 IBM AI Engineering Professional Certificate

2024 IBM Data Science Professional Certificate

For further information on this candidate please use reference number: 055

Request more information

To express your interest or learn more about this candidate please fill out the form below and we will get back to you. Alternatively you can call us on: