Luis – Machine learning, Python, AWS

Senior software engineer for MLOps, Machine Learning infrastructure, Machine Learning engineering, feature extraction, streaming/batch data pipelines preprocessing, vector data bases, data lakes optimization and inference endpoints design.

● Developed 'BobAI' by fine-tuning the Home Depot text using the davinci-003 text model. Implemented FastAPI with Uvicorn for LLM interactions and utilized Airflow -> Kubeflow DSL -> Apache Beam pipeline for continuous model refinement with curated text. Employed prompt engineering techniques with a mix of blend factual and task-based queries, resulting in semantically structured responses without requiring additional handler code. ● Developed the 'Shoppable Images' architecture using Apache Beam, PyTorch, and Kubeflow pipelines. ● Designed workflow orchestration DAGs with Apache Airflow, BigQuery, and Google Cloud Storage (GCS). ● Developed Apache Beam pipelines for ETL/ELT and machine learning purposes. ● Utilized Dataflow pipelines for distributed data processing. ● Incorporated pre-trained TorchVision models for image recognition. ● Implemented cloud functions for event-driven mechanisms.

Senior data engineer for Spark .NET optimization data pipelines and build Data Lake.

● Improved Spark .NET job performance by 36% for the FA-Import project. ● Conducted proof of concept (PoC) for migrating SQL Server external DB to a data lake using S3, leveraging DMS, Glue jobs, Delta Spark, and Athena. ● Proficient in profiling and diagnosing Spark components to identify critical vulnerabilities. ● Conducted scientific research to identify critical breaking points in Spark .NET applications. ● Skilled in Spark optimization techniques and fine-tuning dimensioning.

Software engineer for ML infrastructure, ML engineering and data science.

● Implemented Kubeflow pipelines architecture using Vertex AI; ● Refactored ETL pipelines replacing KFP v1 with KFP v2 (ephemeral components); ● Implemented model metadata tracker and data lineage with Kubeflow ● Designed the 'Prism' torch model pipeline in Kubeflow and Vertex AI. ● Implemented services for managing data processing pipeline on Kubeflow version 1. ● Redesigned and automated a full cycle running ETL process in Kubeflow and GCP environments. ● Successfully debugged and redesigned an ETL project on Kubeflow. ● Migrated Kubeflow components from KFP v1 to KFP v2. ● Created and designed lightweight components. ● Developed event-driven functions using Cloud Functions as sensors for detecting bucket updates

Development of a new reference architecture and business applications that accelerate and enable a better customer experience, adapting the bank's products to real people.

● Optimized Spark data-mining pipeline for improved performance. ● Enhanced efficiency of Spark ML and Mllib jobs through optimization techniques. ● Engaged in Machine Learning engineering activities for distributed systems. ● Carried out responsibilities as a Data Scientist and Machine Learning engineer. ● Developed an Investment product type logit engine. ● Created 'M&Ms' (Minimum & Maximums) left-over balance z-score engine. ● Developed a Markov transition predictor for outlier states engine. ● Implemented Convolution filter for time series smoothing. ● Developed an engine for generating suitable trends for investment plans. ● Implemented and modeled a 360° financial health classification engine 'Check-Up'. ● Conducted research and analysis on Catalyst and Tungsten components for internal documentation. ● Managed task creation, prioritization, and automatic assignment. ● Conducted code reviews to ensure high-quality code standards. ● Collaborated with team members to discuss and review technical solutions. ● Organized local SCRUM meetings for effective project coordination. ● Worked closely with development and DevOps teams. ● Automated day-to-day operations for increased efficiency.

The company provides Flexible Human Capital, Headhunting, Payroll Processing Solutions (PPO), Business & Process Solutions (BPS), Recruitment Process Outsourcing (RPO), and Supplier Management (CWO) services.

● Lead pricing and revenue models & Automated recurrent data mining pipelines with R; ● Implemented regression models for pricing prediction; ● Researched time series from historical sales factors; ● Created new sales strategies based on data analytics and hypothesis testing; ● Implemented a solver for optimizing pricing factors; ● Salesforce analytics with RForcecom library for classification models; ● Implemented training internal moocs for Salesforce adoption.