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@alianderson
Senior Machine Learning engineer delivering scalable AI systems and measurable business ROI.
I am a senior machine learning engineer with over 10 years of experience designing and deploying large-scale AI systems across NLP, computer vision, time series forecasting, and large language models. I combine research-backed development with enterprise delivery to produce production-ready solutions that drive measurable results.
At my current role I built and deployed document intelligence and LLM-based customer support systems, designed multi-agent AutoGPT architectures, and created high-speed computer vision pipelines using YOLOv8 and TensorRT that delivered significant cost savings. I also engineered scalable inference platforms with Ray Serve and FastAPI to handle high-volume, low-latency prediction workloads.
I am passionate about MLOps and cloud-native model lifecycle automation, having implemented SageMaker, Vertex AI, MLflow and Airflow pipelines to reduce deployment cycles from weeks to days. I prioritize pragmatic automation, reproducibility, and delivering ROI through predictive analytics and process optimization.
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Work history, roles, and key accomplishments
DeepVision AI
Jun 2022 - Present (3 years 5 months)
Deployed LLM document-parsing and RAG pipelines that automated 1,200+ manual hours annually and built YOLOv8+TensorRT edge vision solutions delivering $600,000 yearly savings; engineered RayServe/FastAPI inference platform handling 800,000+ daily predictions with <50ms latency.
QuantumScale Labs
Sep 2018 - May 2022 (3 years 8 months)
Built high-throughput NLP and fraud-detection systems processing 6M+ texts/month and protecting assets >$2M; delivered containerized ML pipelines and multicloud serving endpoints using ONNX and FastAPI for continuous delivery.
Cognify AI
Sep 2016 - Aug 2018 (1 year 11 months)
Researched RL and time-series forecasting methods to improve pricing and forecasting accuracy and fine-tuned GPT-2 models (LoRA/QLoRA) for internal chatbot improvements; deployed large-scale training workflows on AWS/VertexAI for 100+ GB datasets.
NexaDevices
Apr 2014 - Aug 2016 (2 years 4 months)
Implemented predictive maintenance and anomaly-detection systems reducing failures and downtime; developed real-time monitoring dashboards and supported distributed GPU training for model experimentation.
Degrees, certifications, and relevant coursework
Master in Computer Science, Computer Science
Completed a Master in Computer Science focusing on advanced machine learning and AI techniques relevant to production-grade systems.
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