Hi, Iām Shams Syed
Machine Learning Engineer
I build scalable ML systems, from data pipelines to production-grade models. My focus areas: deep learning, NLP, generative AI, and MLOps on AWS/GCP/Azure.
Summary
Machine Learning Engineer with end-to-end expertise: data engineering, feature pipelines, model development (CNNs, RNNs, Transformers, diffusion), and production deployment using Docker/Kubernetes and CI/CD. Experienced with LLM fine-tuning, prompt engineering, and retrieval-augmented generation. I turn business problems into measurable ML outcomes.
Skills
PythonRC++SQLJava
PyTorchTensorFlowKerasscikit-learnHugging Face
TransformersBERTGPT spaCyNLTKRAGPrompt Engineering
DockerKubernetesMLflowTFX AirflowSageMakerVertex AIAzure ML SparkKafka
Experience
- Built and deployed NLP/LLM pipelines (GPT, LLaMA) for content automation; reduced cycle time by 40%.
- Trained diffusion models for image synthesis; cut design turnaround by 30%.
- Productionized models on AWS/GCP with CI/CD; improved reliability and scalability.
- Created Tableau/BI dashboards to surface model and business KPIs.
- Optimized ML models (Keras, scikit-learn) achieving 30% latency reduction.
- Built LSTM/GAN pipelines for forecasting and augmentation; retention +40%.
- Managed Spark/Kafka data flows; processing throughput +50%.
- Implemented Kubernetes-based MLOps; deployment reliability +50%.
Projects
Fine-tuned GPT-style model with prompt templates and guardrails; automated campaign copy generation.
Custom Stable Diffusion fine-tuning for brand-specific assets; 30% faster design cycles.
RAG pipeline with embeddings and vector search; accuracy up 25% on internal queries.
Education
Certifications
Contact
Have a project or role in mind? Iām available for full-time and consulting opportunities.