RV Connex

ดูรายละเอียดบริษัท

14 พ.ย. 67

Senior Machine Learning Engineer

สถานที่ปฏิบัติงาน

อ.คลองหลวง จ.ปทุมธานี

เงินเดือน

อัตรา

สมัครงาน

สนใจ

พิมพ์

แชร์

รายละเอียดงาน

Responsibilities 1.Act as an expert in the area of machine learning/statistics. 2.Develop high-performance machine learning systems for detecting abnormality, intrusion, fraud, masquerading. 3.Research and implement machine learning and statistical data mining techniques. 4.Collaboratively architect the system design. 5.Implement machine learning solutions for software security problems on a variety of platforms. 6.Research and prototype algorithms. 7.Design and build real-time systems. 8.As assigned, assumes complete or partial responsibility for one or more tasks that make up the complete project.

คุณสมบัติผู้สมัคร

Bachelor’s Degree or Master’s Degree in e.g. computer engineering, computer science, Machine Learning, Artificial Intelligence, Apply Mathematic or related.
Proficiency with a deep learning framework such as TensorFlow or PyTorch.
Proficiency with Python and basic libraries for machine learning such as scikit-learn and pandas.
Proficiency in Machine Learning Algorithms in a broad range including supervised and unsupervised learning, deep learning, and reinforcement learning.
Expertise in visualizing and manipulating big datasets.
Ability to select hardware to run an ML model with the required latency.
Knowledge in software development life cycle (Preferably experience of traditional methods as well as agile processes).
At least 2 years software development experience.
Experienced in Machine Learning Model Development: Design, develop, and implement advanced machine learning models and algorithms tailored to behavioral analytics, network graph analysis, and peer group analysis.
Behavioral Analytics: Analyze user behavior patterns and trends to create predictive models that drive customer engagement, retention, and personalization strategies.
Network Graph Analysis: Develop and apply network graph algorithms to understand and visualize complex relationships within large datasets, enhancing insights into social, organizational, or transaction networks
Peer Group Analysis: Utilize clustering and comparative analysis techniques to identify and analyze peer groups, driving targeted strategies and optimizing marketing and product development.
Experienced in MapReduce / cluster computing frameworks and libraries, such as Spark, Hadoop
Experienced in MLOps: Oversee the deployment, monitoring, and management of machine learning models in production environments. Implement MLOps best practices to ensure scalable, reliable, and efficient machine learning operations.
Pipeline Development: Design and implement end-to-end ML pipelines, including data preprocessing, model training, validation, and deployment.
Model Monitoring and Maintenance: Set up systems for monitoring model performance, managing model drift, and updating models as needed to ensure continued accuracy and relevance.
Automation: Automate routine ML tasks and workflows to enhance efficiency and reduce manual intervention.
Collaboration: Work with DevOps and engineering teams to integrate ML models into production systems and ensure smooth deployment processes.
Have an analytical mindset and be able to properly analyze data sets to improve the artificial intelligence of their learning systems.
Excellent with Critical Thinking skill, Attention to Detail, Communication and Teamwork.