Daniel Hoyos Email and Phone Number
Daniel Hoyos personal email
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I'm a Lead Machine Learning Engineer with over six years of hands-on experience, specializing in LLMs, NLP, time series forecasting, and ML-driven Predictive Analytics.Current Role: At Blue Orange Digital (NY-based), Developing Copilot For Insights In Partnership with Tungsten Automation, an LLM-based product optimized for enterprise-grade document ingestion and analysis through a conversational interface. In past projects, I've used NLP and GenAI for document optimization, notably for a leading vehicle company utilizing open and proprietary LLMs; I have also done predictive analytics in the marketing space for one of the biggest entertainment companies in the US.Past Experience: At MercadoLibre, Latin America's e-commerce giant, I innovated AWS spot instance forecasting, enhancing infrastructure decision-making and cost-efficiency.Specialties:NLP and LLMs: Developed dialogue systems, OCR, and ASR frameworks. Leveraged text mining and clustering for user insights, emphasizing the Pareto principle. Proficient with models like Transformer, BERT, Roberta, GPT series, and Llama Series, primarily using Hugging Face for open-source models; I've been using them since 2018. Finally, tons of work in the last year and a half with proprietary models from OpenAI and Anthropic. Time Series Forecasting: Tree-based and NN-based forecasting models. The opensource Temporal Fusion, Transformer Pytorch version, is currently being used in the package Pytorch Forecasting.Marketing ML: Devised strategies for predicting churn, attrition, and customer lifetime value, facilitating targeted marketing campaigns.Deep Reinforcement Learning: Applied advanced techniques like DQN, DDPG, REINFORCE, and PPO for real-world continuous state-action scenarios.
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Machine Learning EngineerCanals Ai Jun 2024 - Present -
Tech Lead Machine Learning EngineerBlue Orange Digital Apr 2021 - Jun 2024New York, UsLeading and Developing Copilot for Insights in partnership with Tungsten Automation - an LLM-powered Application for enterprise-grade use for Document Analysis: https://marketplace.kofax.com/details/copilot-for-insights-by-blue-orange-digitalAs the ML Tech Lead, I've worked with one of the biggest vehicle companies, helping them migrate, standardize, and rewrite their requirements automatically using state-of-the-art NLP techniques. I use both Open-Source and Closed-Source solutions, mostly focusing on generative AI.I have also I implemented ML solutions for the marketing team of one of the US's most prominent companies in the Casino industry. Tackling traditional marketing problems such as churn, attrition, customer lifetime value, and customer Decline. Using models such as Linear regression, XGBoost, MLP, and LSTM; working mainly on AWS Sagemaker and EMR for data exploration, cleaning, and feature engineering using Pyspark, Dask, and Pandas; and model training with libraries such as Sklearn, XGBoost, PyTorch, and PyTorch Lightning. Also using AWS Lambda and Glue to create prediction pipelines. -
Sr. Machine Learning EngineerMercado Libre Jul 2020 - Apr 2021Buenos Aires, ArAs the ML Tech Lead of the project, which had the objective of forecasting the amount of AWS spot instances that would be re-claimed to decide which instance types in their particular availability zone are the less risky to use at the time of deploying production applications, whilst reducing infrastructure costs as a resulting factor, I built the solution making several experiments with different model architectures such as gradient boosting models like LightGBM, XGBoost, and deep learning architectures such as LSTM, GRU, self-attention mechanism with the transformer architecture and Temporal Fusion Transformer which was the best model we used when deploying the solution.Created also a custom auto-scaling approach using reinforcement learning creating a dynamic scaling threshold to scale with the CPU utilization percentage and average window. Optimizing the number of instances needed at any particular time for a deployed application. Built KPIs for each project, that were used as a proxy to measure the impact at the solution level and then the follow-up business impact. -
Machine Learning EngineerMillenium Bpo Apr 2018 - Jun 2020Usaquén, Capital District, CoAs one of the Tech leads of the NLP team, I worked on the advancement of getting deeper insights from data from our client's customer interactions with human customer support, using them to build custom Dialog Systems (Chatbots and Voice bots) with a proprietary framework in which I have been a co-creator. This ML solution was deployed to a wide range of clients ranging from Universities, Banking, Electricity providers, Health Insurance, and Hotel chains. All with the purpose of enhancing and automating the biggest pain points of our client's customer support, reducing costs whilst increasing the speed and coverage. -
TutorChegg Inc. Mar 2016 - Oct 2017Santa Clara, Ca, UsTeaching basic math, differential calculus, integral calculus, multivariable calculus, digital signal processing, control systems, machine learning, neural networks and matlab to students around the world through chegg’s web application. Everything was taught in english through written and/or spoken language.
Daniel Hoyos Skills
Daniel Hoyos Education Details
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Universidad Distrital Francisco José De CaldasElectronic Engineering
Frequently Asked Questions about Daniel Hoyos
What company does Daniel Hoyos work for?
Daniel Hoyos works for Canals Ai
What is Daniel Hoyos's role at the current company?
Daniel Hoyos's current role is Machine Learning Engineer @ Canals.ai | AI, ML, Data Science.
What is Daniel Hoyos's email address?
Daniel Hoyos's email address is da****@****ail.com
What schools did Daniel Hoyos attend?
Daniel Hoyos attended Universidad Distrital Francisco José De Caldas.
What are some of Daniel Hoyos's interests?
Daniel Hoyos has interest in Sistemas Difusos, Redes Neuronales, La Inteligencia Computacional, El Control, Complejidad.
What skills is Daniel Hoyos known for?
Daniel Hoyos has skills like Machine Learning, Natural Language Processing, Deep Learning, Inteligencia Artificial, Linux, Sql, Signal Processing, Image Processing, Computer Vision, Data Mining, Data Analysis, Python.
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