MLOps Engineer

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🕒 May 21

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VALCE Talent Solutions

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2016

🤝 B2B

🎯 Recruiter

B2B • Recruitment • Consulting

VALCE Talent Solutions is a company specializing in nearshoring, IT talent acquisition, and consultancy aimed at helping businesses expand globally, particularly in Mexico, LATAM, and the United States. They offer customized solutions that include talent recruitment, workforce management, and the integration of technology and artificial intelligence to enhance business processes. With a strong focus on strategic consulting, VALCE aims to connect technology, talent, and tangible results, boasting a robust network of IT professionals and a proven track record of successful placements and project scaling.

📋 Description

• Design, develop, and deploy machine learning solutions and feature engineering pipelines. • Configure, test, debug, deploy, document, and maintain ML pipelines, models and feature engineering modules while adhering to specific development best practices and quality standards. • Work closely with data scientists, data engineers, and solution architects to develop technical design specifications for ML programs, focusing on efficient feature engineering and model deployment. • Analyze large-scale datasets and validate the proposed ML solutions with both the architectural design and the business needs, ensuring model performance meets target metrics. • Responsible for troubleshooting and issue analysis across the ML stack, including feature pipelines, model training, inference, and model monitoring, as well as coding, testing, and implementing model enhancements. • Demonstrate a strong understanding of supervised, unsupervised, ensemble, and deep learning algorithms to design and implement effective ML solutions, with experience in feature engineering, model evaluation, and continuous performance optimization to meet business targets. • Implement and maintain MLOps practices including experiment tracking, model versioning, A/B testing, and automated retraining pipelines. • Thrive in a fast-paced agile development environment, driving iterative model improvements. • Implement and maintain data governance and model monitoring frameworks to ensure model reliability, fairness, and compliance with business standards. • Available to support/unblock planned model deployments and retraining cycles during off hours. • Contribute to the evolution of our ML architecture, with a focus on MLOps principles and emerging technologies for feature stores.

🎯 Requirements

• 4+ years of professional experience in a ML engineering capacity with focus on production ML systems. • Bachelor's or master's degree in Machine Learning, information technology, Computer Science, or equivalent experience. • Good communication skill (verbal and written) • Experienced on Agile methodology and tools (Jira, Confluence) • Work experience in the Retail industry is a plus

🏖️ Benefits

• competitive salary • flexible work arrangements • professional development opportunities