AI, Machine Learning

Daniel Vargas

Montreal, QC 438-***-**** ******@*****.*** Linkedin Github

SUMMARY

Machine Larning and AI professional with extensive experience in developing and implementing AI solutions to streamline processes and enhance operational efficiency. Proficient in leveraging machine learning, deep learning, and AI technologies to drive innovation in diverse industries such as medical devices, aerospace, and consumer products. Demonstrated expertise in end-to-end AI project management, from data collection to model deployment, with a strong focus on process automation. Experienced in leading cross-functional teams, optimizing AI models, and ensuring compliance with industry regulations.

Areas of Expertise:

Machine Learning, Deep Learning, Artificial Intelligence, and Machine Learning Operations (MLOps)

Large Language Models (LLMs), Prompt Engineering, Generative AI, and Agentic AI

Product Development and Engineering

Process Improvement and Automation

Main Technologies: Python, SQL, Tensorflow / Lite, Pytorch, Azure, Azure, GCP, AWS, OpenAI, Hugging Face, W&B, ONNX, LangChain, RAG, Graph-RAG, MLFLow., LangGraph.

PROFESSIONAL EXPERIENCE

Principal AI Engineer [Freelance] Montreal, QC (Remote)

Lateral AI Jul 2024 – Current

Developed an AI-powered procurement item-matching system for a car parts retailer, utilizing large language models (LLMs + LangChain). This solution reduced matching time by 91.6%, significantly improving procurement efficiency

Delivered an AI-automated grants application system for a technology consulting firm, leveraging AI agents (LangGraph) to reduce processing time per application by 92.5%, enhancing the efficiency of their grant proposal process

AI Advisor Montreal, QC (Remote)

Queva Feb 2024 – Sep 2024

Sr. Machine Learning Engineer Montreal, QC / Costa Mesa, CA (Remote)

FightCamp Oct 2023 – Jun 2024

Designed and implemented the development of the end-to-end machine learning infrastructure and pipeline for human activity recognition (tracking), from data collection to on-device inference

Developed neural networks (CNNs) for detecting and classifying boxing punches and movements using IMU (accelerometer and gyroscope signals) data, with over 95% recognition (Tensorflow Lite)

Deployed models on Android edge devices, optimizing performance and ensuring real-time processing capabilities for over 20k users

Built a Variational Autoencoder (VAE) to generate motion synthetic data, reducing data collection and annotation time

Director, AI Engineering Montreal, QC (Remote)

Innodem Neurosciences Feb 2021 – Oct 2023

Ensured compliance with electronic personal health information (ePHI) privacy and security regulations: HIPAA, PIPEDA, GDPR

Lead the SCRUM process, facilitating daily stand-ups, sprint planning, retrospective meetings, and ensuring that the team is adhering to agile principles and best practices

Managed priorities, ensuring that the team is working on the most critical and impactful features for the business

Sr. Machine Learning Engineer [Contract] Montreal, QC (Remote)

Innodem Neurosciences Feb 2019 – Jan 2021

Trained and delivered neural network (CNN and ResNet) models for eye-tracking applications (Tensorflow, Scikit-Learn, and XGBoost)

Created and operationalized the end-to-end deep learning pipeline (AWS) that covers data engineering and processing, model building, model training and evaluation, and model deployment (Python, SQL)

Implemented model deployment capabilities (MLOps) for both on-server (ONNX, TFLite) and on-the-edge (CoreML, iOS) scenarios, also reducing model deployment cycle time from hours to minutes

Enhanced on-device inference latency, achieving real-time (60 FPS) eye gaze predictions on-device, without losing precision

Engineered on-device model fine-tuning (transfer learning under 5 seconds) code to enable personalized predictions for individual users

Data Science Consultant [Freelance] Remote

Master Data Analysis Sep 2020 – Mar 2023

Designed and facilitated a comprehensive data science training program for a team of 9 data analysts, resulting in a significant increase in team members' technical proficiency and ability to deliver results

Coached and mentored data science projects (banking industry), providing guidance and expert advice, ensuring the achievement of business objectives

Produced all program materials, including code, presentations, assignments, and projects, resulting in a cohesive and effective training program that met the needs of the team and the organization

Setup and managed Azure infrastructure for facilitation sessions and projects execution

Sr. Business Systems Analyst, Operational Technology Montreal, QC

Canadian National Mar 2018 – Dec 2018

Elicited, analyzed, and decomposed over 118 L1 business requirements (process and tools) from internal and external partners

Crafted an NLP model to support requirements management, decreasing elicited requirements redundancy by 8%

Machine Learning Engineer [Freelance] Remote

Aura Heath (Crowdbotics) Nov 2017 – Apr 2018

Developed a recommendation system for an audio streaming service for wellness content, accomplishing over 97% accuracy in recommendations

Project Management Lead, Electrical Systems and Fuel Inerting Montreal, QC

Bombardier Aerospace Jul 2017 – Mar 2018

Supported the team through the initiation, planning, execution, monitoring and control, and closure ofthe different aircraft development phases, handled under the change management process, to ensure completion within the scope, schedule, and budget established in the Statements of Work (SOW) and Product Change Requests (PCR)

Coordinated technical integration activities with input from internal and external (supplier) stakeholders

Continuous Improvement Specialist (ITPLM) Montreal, QC

Bombardier Aerospace Aug 2014 – Jul 2017

Coached and lead continuous improvement projects and workshops (VSM, kaizen, decision-based-schedules, knowledge diagrams, etc.)

oSoftware interface definition documents (IDD) for aircraft builds: lead time reduction from 40 to 30 days, rework rate reduced from 33% to 7%

oStructures dataset release process: first time right rate from 13% to 71%, lead time reduced from 26days to 19 days

oAircraft serialization process: discrepancies from 50% to 0%, ASL 24hr generation turnaround, total manual operations reduced from 111 to 57

oOutsourcing engineering services lead time from 186 to 50 days

oDeveloped a machine learning model to predict most critical load cases from external loads in conceptual design

Lean Six Sigma Black Belt Consultant [Contract] Santo Domingo, D.R.

Quality Global Business Jul 2012 – Dec 2012

Consulting, mentoring and coaching 21 Lean Six Sigma Black Belt projects in two nationwide industrial parks (medical devices, electrical/electronic devices, packaging); for USD$1M+ in yearly savings across 9 companies

Technical Assurance & Validation Engineer II Santo Domingo, D.R.

Johnson & Johnson Nov 2010 – Jul 2012

Establishment of Site Validation Master Plan (VMP) and implementation of new validation procedures and approaches for computerized systems, equipment / process, products, cleaning, facilities / utilities and test methods

Designed and conducted 60+ design of experiments (DOE) to define / improve processes parameters, controls, and limits

Planned and executed 80+ validations focused on process improvement and corrective actions / preventive actions (CAPAs)

Lead Major product packaging improvement (3 product lines), reducing change over time by ~66% and material usage by 21%

CEA Medical Manufacturing Santo Domingo, D.R.

Manufacturing Engineer Jul 2009 – Nov 2010

Successful manufacturing system transfer for: 7 steerable guide wires families, 2 ECG leads families and 3 cryogenic devices families

Lean Six Sigma project for USD$31K+ on yearly savings and over a 2% throughput increase in sub-assemblies manufacturing

Sub-assemblies area re-layout for 23%+ reduction in overall production floor utilization

Process Engineering Supervisor Santo Domingo, D.R.

Andin International Jun 2008 – Apr 2009

Lead project for diamonds usage increase (11%), improving precious stones life cycle and inventory management

Modularization of the workshop-based production system while reducing 16%+ of the assembly space usage

Intermodal and Equipment Control Coordinator Santo Domingo, D.R.

Maersk Line Jul 2007 – Jun 2008

Lead the SAP deployment and implementation in the Caribbean cluster (Central America – Caribbean)

EDUCATION

Machine Learning Engineer Nanodegree Online

Udacity

Data Science Specialization Online

The Johns Hopkins University

MEng. Engineering Management Ottawa, ON

University of Ottawa

BEng. Industrial Engineering Santo Domingo, D.R.

Instituto Tecnologico de Santo Domingo (INTEC)

CERTIFICATIONS

●Generative Adversarial Networks (GANs) – DeepLearning.AI (Jul 2023)

●Natural Language Processing (NLP) – DeepLearning.AI (Jun 2023)

●Machine Learning Engineering for Production (MLOPs) – DeepLearning.AI (Nov 2021)

●Azure Data Scientist Associate – Microsoft (Nov 2020)

●Professional Program in Artificial Intelligence – Microsoft (Jul 2018)

●Deep Learning – DeepLearning.AI (Mar 2018)

●Certified Lean Six Sigma Black Belt (CLSSBB) - Six Sigma Development Group, LLC (Jun 2012)

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