Company Description VMO, a proud member of the ALTEN Group, is part of a global leader in engineering and IT services with over 60,000 employees worldwide. VMO serves as a trusted partner to major global enterprises, including top Fortune 500 companies, driving innovation and digital transformation.
The company's expertise spans consulting, technology, and research, leveraging AI, Data, IoT, and Cloud to deliver impactful solutions. VMO supports clients across industries such as healthcare, finance, and manufacturing, helping them remain competitive in a rapidly evolving digital landscape. With a strong global presence and a track record of large-scale international projects, VMO continues to pioneer smart technology innovations.
Role Description This is a full-time, on-site ML/DA/Gen AI role based in Ho Chi Minh City, Vietnam. The role involves designing, developing, and deploying machine learning and generative AI models for real-world business use cases, including data analysis, prediction, and automation.
Day-to-day tasks include collecting and preprocessing data, building and validating models, implementing scalable ML pipelines, and collaborating with cross-functional teams to integrate solutions into production systems. The role also requires monitoring model performance, optimizing algorithms, documenting technical specifications, and presenting insights and recommendations to stakeholders. The successful candidate will contribute to innovation initiatives, proof-of-concept development, and continuous improvement of AI-driven products and platforms.
Qualifications
Strong foundation in machine learning, deep learning, and generative AI, including experience with common algorithms, model evaluation, and optimization.
Proficiency in programming languages such as Python (and optionally R or Java), and familiarity with ML/AI frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
Solid data analytics and data engineering skills, including data preprocessing, feature engineering, SQL, and working with large datasets.
Experience with cloud platforms and MLOps practices (e.g., CI/CD for ML, model deployment, monitoring) is highly beneficial.
Understanding of
software engineering principles, version control (e.g., Git), and collaborative development workflows.
Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Mathematics, or a related quantitative field.
Ability to communicate complex technical concepts clearly to technical and non-technical stakeholders, and to work effectively in cross-functional teams.
Prior experience in applying ML/AI in domains such as finance, healthcare, manufacturing, or similar industries is a plus.
Curiosity and willingness to continuously learn, explore new AI technologies, and contribute to innovation initiatives.