Machine Learning Engineer

Bayer; Xico; Presencial; MXN 700,000 - 900,000; Jornada completa

Descripción de la vacante

Una empresa farmacéutica global busca un Ingeniero de Aprendizaje Automático en Xico, México, para liderar la transformación de proyectos de ciencia de datos en productos industriales. Se requiere un sólida experiencia en Machine Learning y programación, con un enfoque en la optimización y la colaboración en equipos multidisciplinarios. Los candidatos deben tener al menos un título universitario y habilidades en frameworks de optimización. Se ofrece un puesto de tiempo completo en un entorno dinámico y desafiante.

Formación

• Experiencia de al menos 8 años o un título de máster con 6 años de experiencia.
• Excelentes conocimientos en Machine Learning y programación.
• Experiencia en áreas de gestión de cadena de suministro o fabricación.

Responsabilidades

• Liderar la transformación de prototipos de ciencia de datos a productos industrializados.
• Colaborar con equipos multidisciplinarios en todas las áreas de la cadena de suministro.
• Actuar como embajador digital promoviendo la adopción de estrategias digitales.

Conocimientos

Optimización lineal

Aprendizaje profundo

Programación en Python

Conocimiento de estadísticas

Educación

Título universitario o superior en ciencias exactas

Herramientas

TensorFlow

Descripción del empleo

Machine Learning Engineer

Your task and Responsibilities

• Lead scaling up activities transforming data science prototypes to industrialized end-to-end products by leveraging skills across a wide IT organization and involved operational business process domain experts.
• Perform complex simulation, optimization, modelling and machine learning research integrating multi-layered data models from internal and external sources.
• Collaborate with data scientists, IT product managers and business product owners in all areas of Product Supply like Production, Quality and Supply Chain teams to investigate planning and production behavior and develop data strategies to improve product performance and ultimately quality outcomes.
• Support global product / process owners and IT product managers in analyzing white-spots and business pain points creating opportunities for existing or new data products and cloud solutions to close the discovered gaps and enable new ways of working and decision making.
• Develop and train members of the multi-background team in Data Science topics.
• Act as a digital ambassador facilitating the adoption and absorption of digital and living by example the principles of agile product / project management incl AI and ML principles.

Who you are

• Bachelor's degree with at least eight years of experience or Master's degree with at least six years of experience or Ph.D. with at least three years of experience or comparable.
• Educational or applied experience in machine learning, statistics, applied mathematics, computer science, natural sciences, operations research or another related field.
• Industry experience or very strong academic records leading the delivery of groundbreaking machine learning / advanced analytics projects.
• Broad understanding and experience regarding software development best practices (agile methodology, version control, CI / CD, clean code, MLOps).
• Expert level knowledge in at least one of the following areas: Linear optimization, Bayesian deep learning, Probabilistic Graphical Network, Gaussian processes, MCMC, Reinforcement Learning and / or Deep Learning (RNN, GAN).
• Very good coding knowledge in Python and / or R.
• Proficiency with linear optimization frameworks or machine learning and deep learning frameworks such as TensorFlow.
• Experience with agile methodologies (e.g., SCRUM, DevOps).
• Experience in Pharmaceutical Product Supply process areas like Supply Chain Management, Manufacturing.

Application Period

14 al 28 de Febrero

Referral and Details

• Código de referencia
• División
• Enabling Functions
• Ubicación Mexico : Ciudad de México : Ciudad de México
• Área funcional Tecnología de la información
• Grado de posición VS 1.1
• Tipo de empleo Permanente
• Tiempo de trabajo Full Time