4 дня назад
ML Engineer (Mid-level) (Machine Learning/AI)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
ML Engineer (Mid-level) (Machine Learning/AI): Designing, deploying, and maintaining machine learning models and end-to-end pipelines for large datasets and real-time production environments with an accent on scalability, robustness, and model optimization. Focus on building reliable ML systems, troubleshooting production performance, and researching emerging Machine Learning and AI technologies.
Location: Bangkok, Thailand
Company
is an independent technology consulting firm providing technology guidance and solutions to businesses through an international team across more than 60 countries.
What you will do
- Design, develop, deploy, and maintain machine learning models.
- Build end-to-end pipelines covering data preprocessing, training, evaluation, deployment, and optimization.
- Implement scalable ML solutions for large datasets and real-time environments.
- Monitor and troubleshoot production ML systems to ensure reliability and performance.
- Collaborate with Data Scientists, Engineers, and business stakeholders to translate requirements into effective solutions.
- Research current Machine Learning and AI technologies and introduce relevant innovations.
Requirements
- At least 5 years of experience in Machine Learning Engineering, Data Science, or a related field.
- Hands-on experience developing and deploying machine learning models and building end-to-end ML pipelines.
- Understanding of data preprocessing, model training, evaluation, optimization, and production environments.
- Strong programming, problem-solving, communication, and teamwork skills.
- Ability to work independently, take ownership of technical tasks, and collaborate with technical and business stakeholders.
- English and Thai language skills required.
Culture & Benefits
- International workplace with colleagues from more than 110 nationalities.
- Internal Academy with more than 250 training modules.
- Career development supported by a leadership culture focused on growing talent.
- Regular afterwork gatherings, team-building events, and CSR initiatives.
Hiring process
- Brief virtual or phone call.
- Approximately three interviews, varying by seniority.
- Potential case study, technical assessment, role play, or problem-solving exercise.
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