Fatima T.

★ ★ ★ ★ ★ 4.97 STAR RATING | 100% JOB SUCCESS 💻 SENIOR AI/ML, DATA & BACKEND ENGINEER 🔝 TOP RATED FREELANCER ON UPWORK (40+ COMPLETED PROJECTS) Python ◆ PyTorch ◆ TensorFlow ◆ Scikit-Learn ◆ AWS ◆ GCP ◆ Databricks ◆ PySpark ◆ Docker ◆ Kubernetes ◆ Ray ◆ Terraform ◆ Rag & LLMs ◆ Django ◆ Node.js ◆ TypeScript ◆ GraphQL ◆ PostgreSQL I am a Senior Machine Learning, Data, and Backend Engineer based in Australia with a strong track record of designing, building, and deploying scalable ML pipelines, distributed data architectures, and production-grade backend systems. Over the past several years, I have worked across high-growth fintech and enterprise tech companies including Nearmap, Beforepay Group, and Motive, delivering reliable, high-throughput systems used by millions. My core focus is bridging the gap between complex machine learning models and robust backend infrastructure. On the AI and data side, I specialise in end-to-end model development, explainable tabular modelling (credit risk and predictive analytics), deep learning, distributed training on GPU clusters (Ray, Kubernetes), large-scale batch inference, and production LLM/RAG pipelines. On the backend and cloud side, I architect scalable APIs, microservices, and governed data lakehouses on AWS and GCP using Python, Node.js, TypeScript, Databricks, and Terraform. Whether you need to take an ML model from notebook to production, build a low-latency backend service, or automate your data and MLOps workflows, I focus on writing clean, reproducible, and cost-efficient code. CORE EXPERTiISE & SKILLS: Artificial Intelligence & Machine Learning: Frameworks & Libraries: PyTorch, TensorFlow, Keras, Scikit-Learn, XGBoost, LightGBM, Hugging Face, OpenCV, Pandas, NumPy, SciPy Specialisations: Predictive & Tabular Modelling, Explainable AI (SHAP, Calibration), Deep Learning (CNNs, LSTMs, Temporal Models), NLP, Computer Vision, and Deep Reinforcement Learning (Published IEEE Researcher) Generative AI & LLMs: Custom RAG Pipelines, OpenAI API, Amazon Bedrock, LangChain, Vector Embeddings, Enterprise Question-Answering Systems MLOps, Data Engineering & Cloud Infrastructure: Cloud & Compute: AWS (S3, SageMaker, ECR, EC2), Google Cloud Platform (GCP), Kubernetes, Docker, Ray (Distributed GPU Training on H100/H200/A100) Data Platforms & ETL: Databricks Lakehouse, Snowflake, Apache Spark (PySpark), dbt, End-to-End Data Pipelines, Schema Validation Automation & IaC: Terraform, Terragrunt, CI/CD Pipelines, Experiment Tracking, Automated Feature Engineering, Model Registry & Batch Inference Workflows Backend & Systems Engineering: Languages: Python, TypeScript, JavaScript, SQL, C++ Frameworks & APIs: Django, Flask, FastAPI, Node.js, Express.js, Nest.js, GraphQL (Apollo Server), RESTful APIs, Microservices Architecture Databases: PostgreSQL, MySQL, MongoDB, SQLite, Firebase Frontend Capabilities (For Full-Stack Delivery): React.js, Next.js, GraphQL Client, Tailwind/Material UI My top priority is delivering measurable business impact through solid engineering. If you are looking for an experienced engineer who can take full ownership of your AI/ML systems, data pipelines, or backend architecture, feel free to reach out and let's chat about your project.