Lucas Parisi

Senior Machine Learning Engineer @EFG - ESL Faceit Group

✔️ IT🧑‍🔬 EngineerComputer engineerML EngineerData ScientistData Analyst

Lucas Parisi, as a Senior Machine Learning Engineer at EFG - ESL Faceit Group, is responsible for developing and implementing machine learning models, algorithms, and computational strategies to drive the company's AI initiatives. His work involves managing large datasets, creating predictive models, and ensuring the accuracy and effectiveness of these models. Lucas also collaborates with cross-functional teams to integrate AI capabilities into the company's products and services. His expertise in machine learning, data analysis, and artificial intelligence is instrumental in driving EFG's innovation and growth in the competitive gaming industry.

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Work Background

ESL FACEIT Group - EFGSenior Machine Learning Engineer

Jul. 2024

FreelanceConsultant

Oct. 2014São Paulo Area, BrazilWorked on 40+ cases over the last 5 years providing primary and secondary research and analysis for companies such Parthenon, EY and L.E.K. Consulting for their respective Global Educational Practise.

Defined.aiManager of Machine Learning

Feb. 2024 - Jul. 2024

Defined.aiExpert Machine Learning Enginneer

Nov. 2023 - May. 2024PortugalDevelopment of internal Tools: Batch Prediction Service for internal customers Using Flyte, Ray and Cuda Further improvement of Inference Platform: Speed-up in inference time while reducing costs, increasing throughput 10x. Stack used Ray, FastAPI

Defined.aiSenior Machine Learning Engineer

Jun. 2022 - Nov. 2023Lisbon, Lisbon, Portugal- Maturity Assessment: Conducted comprehensive assessments of MLE and MLOps tools and processes to optimize efficiency and reliability. - Cutting-Edge ASR Research: Spearheaded research, implementation, and evaluation of State-of-the- Art Automatic Speech Recognition (ASR) models, ensuring industry-leading performance. - Question-Answering Agent Development: Successfully developed a Proof of Concept (PoC) utilizing Langchain, OpenAI embeddings, and Llama and Falcon frameworks to create a domain-specific QA agent over a vast document corpus. - Model Fine-Tuning: Employed a supervised approach and Reinforcement Learning from Human Feedback (RLHF) to fine-tune Language Models (LLMs) for enhanced accuracy and adaptability. - Technical Debt Resolution: Investigated and addressed technical debt within APIs, enhancing overall system robustness and maintainability. - Logging and Monitoring Enhancement: Improved system monitoring and logging capabilities, ensuring real-time insights into service performance and model performance. - Legacy Model Versioning: Implemented version control for legacy ASR models using MLFlow, streamlining model management and deployment.

RDMachine Learning Engineering Tech Lead

Oct. 2021 - Jun. 2022- Technical Leadership: Providing visionary technical leadership to drive the development and deployment of machine learning solutions. - Team Coordination: Orchestrating and coordinating multidisciplinary teams of Data Scientists, Engineers, and DevOps professionals to ensure seamless collaboration. - MLOps Architecture: Designing and implementing robust MLOps architectures to optimize model development, deployment, and monitoring. - Scalability: Pioneering strategies to scale machine learning products, ensuring they can handle increased workloads and data volumes. Innovation: Encouraging a culture of innovation, experimentation, and continuous learning to stay at the forefront of AI technology. - Problem Solving: Tackling complex technical challenges, from model optimization to system architecture, to deliver solutions that exceed expectations. - Mentorship: Nurturing talent through mentorship, fostering the growth of team members and contributing to their professional development. Strategic Planning: Developing long-term strategies for leveraging AI and machine learning to meet business objectives.

RDMachine Learning Engineer

Nov. 2020 - Oct. 2021São Paulo, BrazilMy role as a liaison between Data Engineers, Data Scientists, and Architects has been pivotal in achieving seamless cloud integration of machine learning products. Here are some key contributions: - Cross-Functional Collaboration: Facilitated effective communication and collaboration between Data Engineers, Data Scientists, and Architects to bridge the gap between data science and cloud deployment. - MLOps Architecture Design: Designed and implemented robust MLOps architecture within the AWS datalake framework, optimizing scalability, performance, and security. - Datapipeline Expertise: Architected, supported, and maintained critical data pipelines crucial for the feature store, model training, and inference pipelines, ensuring data availability and reliability. - Model Migration to the Cloud: Assisted Data Scientists in migrating their models to the cloud environment, enabling them to leverage the full potential of cloud resources. - Mindset Transformation: Spearheaded an initiative to shift the Data Scientists' mindset from local to enterprise, fostering a culture of cloud-first thinking and enhancing efficiency in model development and deployment.

RDData Scientist

Jan. 2020 - Nov. 2020São Paulo Area, BrazilPoint-of-Contact for the customers record linkeage cloud application called VUC. VUC enables the company to have customer's instead of the transaction view. This allows the company to focus on the client experience and journey. Exclusive offers, customer segmentation and hypercustomization are enabled by this application. Expertise with XGBoost, ElasticSearch, SQS.

BeegolData Scientist

Sep. 2019 - Jan. 2020São Paulo Area, BrazilData scientist creating machine learning products, developing solutions for retail. Solving product recommendation and demand forecasting problems - Machine learning techniques used: XGBoost, LSTM, deep neural networks, cluster, sets; - Data analysis using advanced statistical techniques; - Creation and monitoring of KPIs and indicators; - Software development with scalability and performance; - Adaptation of state-of-the-art research for use in products; - ETL development; - Data visualization; - Agile methodology in project development.

RDData Scientist

Jun. 2019 - Sep. 2019São Paulo Area, BrazilDeep Learning Computer Vision planogram compliance implementation

Sintel S.AAnalista de Suporte

Mar. 2012 - Oct. 2012São Paulo Area, Brazil Application monitoring of in-house suite of products to support EDI between car manufacturers and its respective supply chain. Ticket resolution via Service Desk Remote support via VPN, Terminal Services, LogMe in, VNC, Cytrix Direct contact with the costumer over phone/e-mail

IBMIT Specialist

Sep. 2010 - Aug. 2011HortolândiaIT Specialist for Sprint/Nextel @ IBM Production support of more than 10 usiness critical applications. Re-image, configuration, support and cycle 0 for both application and hardware level Remote support for ground teams of technicians Database queries and investigation

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