Andy Rosales-Elias

Senior Software Engineer

Brooklyn, New York, United States10 yrs experience

Most Likely To SwitchHighly Stable

Key Highlights

Expert in Machine Learning and Software Development.
Led multiple high-impact projects at Lyft.
Strong background in agricultural technology innovations.

Stackforce AI infers this person is a Machine Learning Engineer specializing in SaaS and Agritech solutions.

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Skills

Core Skills

Machine LearningSoftware Development

Other Skills

PythonFlaskAlgorithmsC++GitAirflowSparkFugueKubernetesREST APIFront-end DevelopmentBack-end DevelopmentIoTCloud ComputingComputer Vision

Experience

10 yrs

Total Experience

3 yrs 1 mo

Average Tenure

6 yrs 4 mos

Current Experience

Lyft

3 roles

Senior Software Engineer, ML Platform

Promoted

Apr 2023 – Present · 3 yrs 1 mo

Built AI Assistant Platform for querying domain-specific knowledge using context-augmentation techniques like RAG, powering documentation chatbots and processing thousands of internal daily requests across multiple environments.
Led development of a company-wide anomaly detection system that detects both sudden spikes and gradual changes in incident rates, built on Airflow, Fugue and Spark -- seamlessly integrated with LyftLearn's training infrastructure.
Led development of Model Monitoring system to track a "Model Health Score" based on freshness metrics, query patterns, and key performance indicators.

Machine LearningPythonFlaskAlgorithmsC++Git+1

Software Engineer, ML Platform

Apr 2020 – Apr 2023 · 3 yrs

* Lead engineer for Lyftlearn: Lyft's ML training infrastructure built on Kubernetes. Lyftlearn enables dozens of teams to develop, train, and deploy machine learning models across critical business functions including dispatch, pricing, fraud detection, and support. Supporting diverse modeling libraries (sklearn, LightGBM, XGBoost, PyTorch, TensorFlow) while leveraging Kubernetes, Spark, and Fugue for distributed training at scale.

KubernetesMachine LearningSparkFuguePythonSoftware Development

Software Engineering Intern

Jun 2019 – Sep 2019 · 3 mos · San Francisco Bay Area

Designed, implemented, and tested the backend for a new metrics tool used in Lyft’s Machine Learning Platform, which displays and tracks the performance of online ML models over time.

PythonMachine Learning

Intouch health

DevOps Intern

Apr 2019 – Jun 2019 · 2 mos · Santa Barbara, California Area

- Improving front-end, and back-end aspects of Device Manager, an InTouch Health tool that serves as interface and REST API for monitoring, managing, and updating medical devices.

REST APIFront-end DevelopmentBack-end Development

Github

Machine Learning Intern

Jun 2018 – Sep 2018 · 3 mos · San Francisco Bay Area

Used NLP techniques to do large-scale analysis on source code
Created an application that detects duplicate source code using NLP
Explored, collected and cleaned a code duplication dataset for the entire team to use on various project
Created a formal report containing about code duplication detection for the teams future use

Intel corporation

2 roles

ML Software Engineering Intern

Jun 2017 – Sep 2017 · 3 mos

Worked with different deep learning frameworks and VR technologies for exercise & fitness
Used image processing techniques and computer vision DL algorithms

AI Campus Ambassador

Sep 2016 – Jan 2019 · 2 yrs 4 mos

Represent and make use of Intel's Artificial Intelligence technologies (e.g Movidius, Nervana)
Present my research during Intel sponsored events
Bring awareness of Intel AI technology to my campus through workshops and info sessions

Uc santa barbara

2 roles

Undergraduate Researcher

Jun 2016 – Jun 2019 · 3 yrs

Part of a team working on SmartFarm - a tool that uses modern technology (IoT, cloud computing) to increase agricultural sustainability.
Current project: ”Where’s the bear?” a tool that uses machine learning based image recognition for animal detection using convolutional neural networks. (Caffe & TensorFlow).
Successfully contributed an OCR tool that reads temperature values from an image using the k-Nearest Neighbor algorithm with 100% accuracy, 5 times faster than the previous tool.
Use of several techniques to obtain labeled training data for the supervised classification model.
Conducted research presentation and created a poster to showcase data.

Student Administrative Assistant

Oct 2015 – Jun 2016 · 8 mos

Helped in several aspects of the office, such as computer support, social media, and projects.
Successfully set up a web-based system for departmental room reservations. (see more details in projects section)
Improved the department’s website by re-modeling specific pages.

Machine LearningIoTCloud Computing

California nanosystems institute (cnsi)

Summer Institute of Math and Science Intern

Aug 2015 – Aug 2015 · 0 mo · Santa Barbara, California Area

32 incoming freshman were selected to participate in an intensive, research summer program. This program consisted of: taking three courses, calculus, physics and writing. conducting research with a team of 3 other interns and a graduate student mentor. research presentation that showcased our data/achievements for the program.
Conducted undergraduate research on Machine Learning and its applications on Optical Character Recognition under a graduate student mentor to deliver a final presentation.
Built an unsupervised learning model that recognized the handwritten characters 0-9 in 100 seconds with 96% accuracy. (see details in projects)
Conducted a formal research presentation in front of 60+ audience members.