Machine Learning Engineer Manager

2 weeks ago

Hong Kong Island, Hong Kong SAR China Intellectsoft Full time
Responsibilities
The successful candidate will be responsible for:

- Designing the architecture for the open-source-based data analytics platform;
- Developing scalable data models, data pipelines, and data lakes;
- Ensuring integration of various data sources, including Kafka, NiFi, Apache Airflow, and Spark;
- Implementing modern data platform components like Apache Iceberg, Delta Lake, ClickHouse, and PostgreSQL;
- Defining and enforcing data governance, security, and compliance best practices;
- Optimizing data storage, access, and retrieval for performance and scalability;
- Collaborating with data scientists, engineers, and business analysts to ensure platform usability;

Requirements
We are looking for a highly motivated and experienced professional who possesses the following qualifications:

- 7+ years of experience in data science, machine learning, and statistical modeling;
- Strong programming skills in Python, SQL, and Spark;
- Hands-on experience with MLflow, PyTorch, Spark MLlib, and FastAPI for model development and deployment;
- Understanding of distributed computing and big data processing using Apache Spark and ClickHouse;
- Proficiency in feature engineering, data preprocessing, and model tuning for large-scale datasets;
- Experience in building and deploying ML models in production environments using TorchServe, FastAPI, or similar frameworks;
- Knowledge of deep learning architectures (CNNs, RNNs, transformers) and their practical applications;
- Strong grasp of MLOps best practices, including CI/CD for ML models, model monitoring, and retraining pipelines;
- Understanding of real-time analytics and event-driven architectures for processing streaming data;
- Experience working with SQL and NoSQL databases such as PostgreSQL, ClickHouse, and Delta Lake;
- Strong ability to collaborate with data engineers, architects, and business analysts to ensure ML models align with business objectives;
- Knowledge of A/B testing methodologies and causal inference techniques for evaluating model effectiveness;
- Familiarity with cloud services (AWS, GCP, or Azure) for scalable model training and deployment;

Benefits
We offer a range of benefits to our employees, including:

- 35 absence days per year for work-life balance;
- Udemy courses of your choice;
- English courses with native-speaker;
- Regular soft-skills trainings;
- Excellence Centers meetups;
- Online/offline team-buildings;

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