เงื่อนไขการค้นหา

ประสบการณ์:

3 ปีขึ้นไป

ทักษะ:

Industry trends, SQL, NoSQL, English

ประเภทงาน:

งานประจำ

• Design and work on all aspects of bringing ML models into production, develop CI/CD pipelines by collaborating with other disciplines such as data engineering, application development, cloud infrastructure, and security to implement AI solutions in production.
• Work collaboratively with data scientists along the machine learning lifecycle from data pipeline, data preparation, model deployment, and model monitoring.
• Understand and assess AI/ML industry trends to leverage technologies, continuously i ...
• Provide architectural and technical leadership to drive AI/ML capabilities.
• Initiate innovation and development projects to continuously improve the overall efficiency of the team in the engineering aspect.
• Professional Knowledge & Experiences.
• Degree in computer science or related fields, with concentration in Machine Learning/AI engineering.
• At least 3 years of experience in implementing and deploying Machine Learning solutions (using various models, such as Linear/Logistic Regression, Support Vector Machines, Neural Networks, etc.). Expertise with Data Science and experience with manipulating/transforming data, model selection, model training, and deployment at scale.
• Knowledge and experience in database technologies, such as SQL, NoSQL, and demonstrate knowledge of databases (Google BigQuery preferred), Data ETL framework (Airflow), ML libraries (scikit-learn, XG Boost, PyTorch, etc.), ML Frameworks (Kubeflow, MLFlow, etc.).
• Knowledge and experience in Kubernetes technology. Be able to develop CI/CD pipeline, deploy workloads, configure and monitor jobs on kubernetes clusters.
• Significant proficiency in Python. Experience working with GCP is preferrable.
• Ability to work in cross functional teams, have team-work mindset, self-motivation.
• Excellent written and verbal communication skills in English.
• Additional Desirable Qualification.
• Solid grounding in statistics, probability theory, data modelling, machine learning algorithms and software development techniques and languages used to implement analytics solutions.
• Extensive background in statistical analysis and modeling (distributions, hypothesis testing, probability theory, etc.).
• CORE Competencies.

ประสบการณ์:

2 ปีขึ้นไป

ทักษะ:

Research, Python, SQL

ประเภทงาน:

งานประจำ

• Develop machine learning models such as credit model, income estimation model and fraud model.
• Research on cutting-edge technology to enhance existing model performance.
• Explore and conduct feature engineering on existing data set (telco data, retail store data, loan approval data).
• Develop sentimental analysis model in order to support collection strategy.
• Bachelor Degree in Computer Science, Operations Research, Engineering, or related quantitative discipline.
• 2-5 years of experiences in programming languages such as Python, SQL or Scala.
• 5+ years of hands-on experience in building & implementing AI/ML solutions for senior role.
• Experience with python libraries - Numpy, scikit-learn, OpenCV, Tensorflow, Pytorch, Flask, Django.
• Experience with source version control (Git, Bitbucket).
• Proven knowledge on Rest API, Docker, Google Big Query, VScode.
• Strong analytical skills and data-driven thinking.
• Strong understanding of quantitative analysis methods in relation to financial institutions.
• Ability to clearly communicate modeling results to a wide range of audiences.
• Nice to have.
• Experience in image processing or natural language processing (NLP).
• Solid understanding in collection model.
• Familiar with MLOps concepts.