# Julian A. > MIT Math | 5G-TSN Real-time Streaming Communications | Simulations | Vision/ML APIs Python Engineer | Cloud | Legal | Location: Greater Boston, United States Profile: https://flows.cv/juliana1 Python Programmer/ML Engineer/Data scientist experienced in the full machine learning pipeline from data collecting/scraping, training, to deployment and serving at scale. Experienced in deep learning: which is promising in that neural nets occupy constant space and can automatically learn 'abstraction'. Python/Linux programmer of 7+ years. Machine Learning person of 7+ years. MIT Math graduate with programming experience at NASA and MIT. Strengths are Python (Numpy,Scikit,Machine Learning). Authored a programming Machine Learning Book: scikit-learn Cookbook. Additionally, have experience writing math textbooks. Key Achievements include 10,000X+ speed up in XML code production, initiating Machine Learning at the Harvard based programming Computer Vision start-up, Ayaakua LLC, and winning a three state competition in programming and Chemistry. ## Work Experience ### Machine Learning Engineer @ Consulting Jan 2019 – Present • Design and serve Machine Learning model which deals with missing values within a week of time: reduced customer costs by over 50%: thereby generating a budget to figure out how to generate more budgets :) Skills: • Machine Learning • Python ### Chief Technology Officer @ Consulting Jan 2022 – Jan 2023 ### scikit-learn Cookbook @ Packt Jan 2017 – Present | London, United Kingdom Programming Code & Result Oriented Book about Artificial Intelligence and Machine Learning. Main focus is Meta-Learners: Stacker Aggregators, Gradient Boosted Trees, Ensembles,... I also talk about neural networks, natural language processing, and object-oriented-programming for Machine Learning. Skills: • Machine Learning • Python AI Rewrite: • Authored the "scikit-learn Cookbook," focusing on practical applications of Artificial Intelligence and Machine Learning. • Explored advanced topics such as Meta-Learners, Stacker Aggregators, and Gradient Boosted Trees. • Provided insights into neural networks, natural language processing, and object-oriented programming for Machine Learning. • Collaborated with Packt, a leading publisher in technology, to deliver valuable content to developers and data scientists. ### Lead Software Engineer Consultant @ Verizon Business Jan 2023 – Jan 2025 | Boston, MA ### Robotics Software @ Berkshire Grey Jan 2021 – Jan 2022 Increase Fortune 50 customer productivity 3X+ at points on the logistical pipeline. Do this by designing, programming, and deploying robots. ### Lecturer of Graduate Course | Thesis Advisor @ Harvard University Jan 2018 – Jan 2021 | Cambridge, Massachusetts Programming and practical Computer Science lecturer and thesis advisor. • Lecture about building practical products with Python/Linux/Solidity. Help 100+ industry veterans program Blockchain prototypes. • Thesis advisor: successfully guide student to develop Blockchain prototype to not waste electricity. • Hire teaching assistants to grade papers and run sections. Develop the research and presentation skills of teaching assistants based on their strengths. • Natural Language Processing: advise student in using neural network embeddings. Advise student to set up Apache Spark infrastructure on Google Cloud. ### Senior Member Of Technical Staff @ Pickle Robot Company Jan 2020 – Jan 2021 | Cambridge, Massachusetts Build Computer Vision AI allowing robot arm to grasp objects from clutter or off a conveyor. Pickle is building robots that help your packages move through the logistics pipeline much more efficiently and at a lower cost. ### ML Workflow Engineer | Machine Learning Engineer | Data Scientist (Consultant - Remote) @ Google Jan 2019 – Jan 2019 | Mountain View, California PoC, Build, Deploy: Anomaly Detector Fix, Deploy: Other stuff like FAISS Wrapping Working on development of Google's AI Hub. ML Workflow Engineer. Autoencoders and VAEs are very interesting representational neural networks. Autoencoders are used to find anomalies in domains such as fraud detection, energy, network intrusion & security, cancer research, and commodity trading. Skills: • Machine Learning • Python • GCP (Google Cloud Platform) ### Data Scientist @ Cinelytic, Inc Jan 2016 – Jan 2019 • Built complex AI/ML system in production to predict movie revenues. • Work featured in deeplearning.ai (an Andrew Ng company) newsletter. • Work in the news here: https://www.hollywoodreporter.com/news/warner-bros-signs-deal-ai-driven-film-management-system-1268036 Skills: • Machine Learning • Python ### YOLO neural network for Videos @ Consultant Jan 2018 – Jan 2018 | New York City Develop optimized real-time object detection system on videos with YOLO neural-net. Skills: • Machine Learning • NumPy • SciPy • OpenCV • Python ### Senior Financial Quantitive Analyst @ Acura Capital Jan 2016 – Jan 2018 ### Data Scientist @ Intrigma Inc. Jan 2017 – Jan 2017 | New York - Made a Visualization Business App for Windows OS. - Visualized outputs and algorithm scenarios to inform myself and other programmers in regards to C development. ### Data Scientist @ Ager Analytics Jan 2017 – Jan 2017 | San Francisco Bay Area - Perform MapD SQL queries with the Python API for data analysis. Integrate the queries as a first step to a more complete data analysis. Skills: • Machine Learning • Python ### Consultant: Deep Neural Networks: AI @ Gen.Life Limited Jan 2017 – Jan 2017 | Palo Alto • Deep Learning: Developer of Computer Vision Prototypes using Convolutional Neural Nets. • Use Python and Ubuntu Linux Shell on AWS. • Successfully built a prototype for an innovative product. • PyTorch, Numpy, OpenCV, and other libraries • Realtime Production Inference on Video Streams Skills: • Machine Learning • Python ### Machine Learning Engineer @ Accern Jan 2016 – Jan 2016 • Develop backtests following high standards for hedge funds. The best backtest has a Sharpe Ratio of 3.14, Beta of 0.92, and Drawdown of -6.2%. Use high quality Accern sentiment news data. • Manage files of data with 5 million rows to aid stock trading. ### Lecturer @ Russian School of Mathematics Jan 2014 – Jan 2016 | Lexington, MA ### Consultant: Analyst and Programmer @ Ayaakua, LLC Jan 2014 – Jan 2016 | Cambridge, MA Program and design algorithms dealing with Computer Vision and Data Analysis. Products deal with a machine’s understanding of a 3-dimensional visual scene and the data analysis of customer data. Skills: • Machine Learning • Python • JavaScript: Three.js API ### Algorithm Developer @ Crowdkast Jan 2016 – Jan 2016 Program to implement stock-market trading strategies using high-quality sentiment data. Python: Pandas, Numpy. Construct trading strategies using sentiment data. • Design stock-trading strategies (with the lead quant) and make a stock trading strategy profitable with Returns: 206.3%, Sharpe Ratio of 2.38, Drawdown of -14.8% over four years in back-testing using Crowdkast’s data. Data is derived from real views of stock market participants and consequently it is valuable for algorithmic trading. Demonstrated the power of crowd-sourcing in generating predictive earnings forecasts, volatility forecasts, and target prices. The proprietary volatility data outperforms traditional volatility metrics when applied to algorithmic trading. ### Content Dev @ GEX Jan 2013 – Jan 2014 • Program interactive math problems. • Write probability/stats parts of math textbooks exposed internationally ## Education ### Mathematics in Mathematics, Physics, Computer Science Massachusetts Institute of Technology ### Mathematics classes in Mathematics Harvard University ## Contact & Social - LinkedIn: https://linkedin.com/in/julian-avila-machine-learning --- Source: https://flows.cv/juliana1 JSON Resume: https://flows.cv/juliana1/resume.json Last updated: 2026-03-31