Technical skills
PythonJavaData engineeringData analysisBusiness intelligenceData scienceCI/CDGoogle CloudDockerKubernetes
Responsibilities
- Develop machine learning models and algorithms to address business needs.
- Collaborate with data scientists and software engineers to design and implement scalable and efficient solutions.
- Clean, preprocess, and analyze large datasets to extract meaningful insights.
- Deploy machine learning models into production environments and monitor their performance.
- Continuously improve model accuracy and performance through experimentation and optimization.
- Stay up-to-date with the latest advancements in machine learning and related technologies.
- Communicate findings and results to stakeholders in a clear and concise manner.
Requirements
- Bachelor's degree or higher in Computer Science, Engineering, Mathematics, or a related field.
- 2~5 years of experience in machine learning, data science, or a related field.
- Proficiency in programming languages such as Python, Java, or Scala.
- Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, or scikit-learn.
- Strong understanding of machine learning algorithms and techniques, including supervised and unsupervised learning, deep learning, and reinforcement learning.
- Experience with cloud platforms such as Google Cloud Platform (GCP), including services like BigQuery, Cloud Storage, and AI Platform.
- GCP Professional Machine Learning Engineer certification is required.
- Experience with version control systems such as Git.
- Excellent problem-solving skills and attention to detail.
- Strong communication and collaboration skills.
Preferred Qualifications
- Master's degree or higher in Computer Science, Engineering, Mathematics, or a related field.
- Experience with distributed computing frameworks such as Apache Spark.
- Familiarity with containerization and orchestration technologies such as Docker and Kubernetes.
- Experience with data visualization tools such as Matplotlib, Seaborn, or Tableau.
- Experience with natural language processing (NLP) or computer vision (CV) techniques.
- Experience with continuous integration and continuous deployment (CI/CD) pipelines.
- Contributions to open-source projects or participation in relevant communities.