**ml solution architect**: bogotá, capital district, medellín, antioquia, san jose **about project** **provectus **helps companies adopt ml/ai to transform the ways they operate, compete, and drive value. the focus of the company is on building ml infrastructure to drive end-to-end ai transformations, assisting businesses in adopting the right ai use cases, and scaling their ai initiatives organization-wide in such industries as healthcare & life sciences, retail & cpg, media & entertainment, manufacturing, and internet businesses. as a solutions architect, you will be responsible for designing, planning, and implementing scalable, cloud-based, and on-premise data and ml architectures. you will collaborate with internal teams, clients, and stakeholders to build state-of-the-art solutions across big data, machine learning, and real-time analytics environments. your role will focus on delivering high-quality, innovative solutions while adhering to best practices in architecture, security, and compliance. this role also requires providing strategic technical leadership on complex, high-impact customer engagements. you will design advanced technical solutions, manage technical risks, and collaborate with cross-functional teams to ensure successful solution delivery. your role will involve driving innovation, optimizing customer kpis, and mentoring other architects and technical leaders. **responsibilities**: - lead the design and implementation of data and ai/ml architecture solutions across cloud and on-premise platforms. - lead complex customer engagements, prov...
Provectus helps companies adopt ml/ai to transform the ways they operate, compete, and drive value. the focus of the company is on building ml infrastructure to drive end-to-end ai transformations, assisting businesses in adopting the right ai use cases, and scaling their ai initiatives organization-wide in industries such as healthcare & life sciences, retail & cpg, media & entertainment, manufacturing, and internet businesses. the role of a practice leader is crucial for the company’s machine learning practice because it involves not only managing people but also ensuring tasks are completed. a practice leader must have sufficient technical experience to uphold and demonstrate best market practices while staying updated with the latest technologies. requirements: candidates should combine strong software engineering experience for ml applications with proven people management skills. strong understanding of ml project lifecycle. experience in one or more of the following areas: nlp, cv, forecasting, recommender systems, reinforcement learning. experience in productionizing ml models across different modalities. experience with developing deep learning models from scratch. ability to create reusable components for ml pipelines. ability to justify and explain design decisions. practical experience with model post-production & maintenance, including monitoring and retraining automation. experience with cloud platforms such as aws, open-source alternatives, mlops platforms, frameworks, and libraries. strong understanding of python patterns & best practices. experience in crea...
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