Machine Learning Engineer
99
Date: 3 days ago
Area: Singapore, Singapore
Contract type: Full time
At 99 Group, we're on a mission to revolutionize the real estate industry by seamlessly integrating cutting-edge technology and innovation. If you're excited to be at the forefront of this transformation and are ready to tackle the industry's challenges head-on, we want you to be a part of our dynamic team.
As a Machine Learning Engineer, you will be responsible for building and deploying machine learning models that solve complex problems in home price estimation, natural language processing, listings recommendation and image/object detection. You will collaborate closely with data science and engineering teams to ensure our models are not only accurate but also scalable and production-ready. Your work will directly impact our ability to make intelligent, data-driven decisions and provide real-time predictions to our users.
What You'll Be Doing
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As a Machine Learning Engineer, you will be responsible for building and deploying machine learning models that solve complex problems in home price estimation, natural language processing, listings recommendation and image/object detection. You will collaborate closely with data science and engineering teams to ensure our models are not only accurate but also scalable and production-ready. Your work will directly impact our ability to make intelligent, data-driven decisions and provide real-time predictions to our users.
What You'll Be Doing
- Design, develop, and deploy machine learning models for real-time regression, classification, and object detection tasks.
- Collaborate with data scientists to build, train, and optimize models using frameworks like TensorFlow, PyTorch, or Scikit-learn.
- Implement model serving pipelines for deployment in Kubernetes environments, using Docker and orchestration tools.
- Develop and maintain scalable machine learning APIs to serve predictions and integrate them with client applications.
- Automate data preprocessing, feature extraction, and model training pipelines using tools like Airflow, Argo, Kubeflow, or similar.
- Monitor the performance of deployed models and implement updates to maintain accuracy and efficiency over time.
- Work closely with DevOps/Engineering to ensure smooth model integration into production environments.
- Conduct code reviews, write unit tests, and maintain high code quality and documentation.
- Stay updated with the latest research and advancements in machine learning and AI technologies.
- 3+ years of experience in machine learning, model deployment, or a similar role.
- Proficiency in Python, with experience in libraries like TensorFlow, PyTorch, and Scikit-learn.
- Strong knowledge of data processing frameworks (Pandas, Numpy) and experience working with large-scale datasets, both structured and unstructured.
- Hands-on experience in deploying machine learning models in production using Docker and Kubernetes.
- Experience in building and deploying RESTful APIs for machine learning models.
- Experience working with cloud platforms (AWS, GCP, or Azure) for model deployment and scaling.
- Familiarity with Git and CI/CD pipelines.
- Bonus: Experience with MLOps tools like Airflow, Argo, Kubeflow, or MLflow for workflow automation and monitoring.
- Experience in image recognition and object detection using CNNs, YOLO, or similar architectures.
- Familiarity with distributed systems and parallel processing (e.g., Spark, Dask).
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