MLOps resume sample

• Managed the lifecycle of machine learning products, focusing on model training, serving, and monitoring at scale.
• Developed solutions to enhance the scalability and efficiency of machine learning models.
• Collaborated with cross-functional teams to ensure seamless integration and operation of ML models.
• Automated deployment pipelines to ensure continuous delivery of machine learning models.
• Optimized existing machine learning infrastructure, reducing latency and improving model performance.

• Led the renewal of the ECS data lake, including the architecture proposal and construction of ETL pipelines.
• Developed machine learning models to guide business decisions and optimize processes across the company.
• Collaborated with the Growth team to implement data-driven strategies and models.
• Implemented real-time data processing solutions, enhancing the speed and accuracy of decision-making.
• Provided technical mentorship to junior engineers.

• Guided and supported multiple projects, including the integration of Alexa skills with laboratory systems.
• Developed back-end solutions using .NET and front-end components using React.
• Implemented continuous integration and deployment processes using Azure.
• Designed and optimized database structures to support scalable applications.
• Led code review sessions, ensuring adherence to best practices and high-quality code standards.

• Led the development of APIs for BS2 bank HUB, Serasa Experian’s eCred marketplace, and other major clients.
• Architected data lake structures and defined storage and consumption strategies for Serasa’s Polis platform.
• Managed the AI guild, organizing events and content creation for the team’s development.
• Spearheaded the adoption of microservices architecture, enhancing system modularity.
• Collaborated with stakeholders to translate business requirements into technical solutions.

• Played a key role in the renewal of the ECS data lake, focusing on ETL pipeline construction and data architecture.
• Contributed to the Growth team by developing models that informed company-wide business decisions.
• Integrated multiple data sources into the data lake, improving data accessibility for analysis.
• Developed and maintained data quality checks to ensure the accuracy of ingested data.

• Led the DTI team responsible for creating architecture in the BS2 HUB project.
• Developed microservices in .NET core, utilizing queues and SQL databases.
• Managed project timelines and deliverables, ensuring on-time completion of key milestones.
• Collaborated with cross-functional teams to ensure alignment on project goals.

• Developed machine learning algorithms for market positioning using Python, sklearn, and xgboost.
• Implemented feature engineering, forecasting, and risk management techniques to optimize trading strategies.
• Automated testing and monitoring strategies for investment bots using pytest.
• Analyzed market data to develop predictive models that informed trading decisions.
• Worked closely with the finance team to align machine learning models with investment strategies.

• Developed Excel plug-ins in C# and algorithms in VBA for data analysis and user interaction.
• Managed the team responsible for developing the company’s sales system, applying agile methodologies.
• Developed back-end applications and supervised front-end and database teams.
• Designed and implemented database models to support business operations.
• Assisted in the deployment of software solutions, ensuring smooth integration with existing systems.

• Assisted in data management and analysis tasks to support operational efficiency.
• Contributed to various projects aimed at improving process workflows and data accuracy.
• Supported inventory management by developing tools for data tracking and reporting.
• Participated in team meetings, providing insights and suggestions for process improvements.