Machine Learning Engineer

We are looking for a talented MLOps Engineer to join our production team, specializing in implementing cutting-edge generative AI and machine learning applications. The ideal candidate will have hands-on experience with tools such as Microsoft OpenAI, Domino Data Lab, and Mistral models. This role requires the ability to identify differences between various models, monitor their performance, and collaborate closely with application teams to share knowledge and best practices.

• Collaborate with data scientists and software engineers to Implement and optimize generative AI and machine learning models in production environments.
• Provision & manage the infrastructure required for hosting ML models, including cloud resources and on-premises servers.
• Utilize containerization technologies like Docker to package models and dependencies.
• Develop and maintain CI/CD pipelines for automating the testing, integration, and deployment of ML models.
• Implement version control to track changes in both code and model artifacts.
• Optimize existing models for performance and scalability.
• Establish monitoring solutions to track the performance and health of deployed models.
• Set up logging mechanisms to capture relevant information for debugging and auditing purposes.
• Ensure compliance regulations and data protection standards.
• Document processes, methodologies, and results for transparency and reproducibility.

• Total 7+ years of overall IT experience.
• Architecture and deployment of solutions on cloud platforms like Azure/AWS or GCP.
• Proficient in machine learning algorithms, models, and statistical concepts.
• Knowledge of data preprocessing techniques and feature extraction.
• Experience with generative AI tools (e.g., Microsoft OpenAI, Domino Data Lab).
• Skilled in MLOps frameworks (e.g., Kubeflow, MLFlow, DataRobot, Airflow).
• Docker and Kubernetes, OpenShift for container management and scaling.
• Proficient in programming languages (Python, Go, Ruby, Bash) and Linux.
• Familiarity with machine learning frameworks (scikit-learn, Keras, PyTorch, TensorFlow).
• Experience with CI/CD pipelines.
• Knowledge of IaC tools (e.g., Terraform, CloudFormation) and configuration management tools (e.g., Ansible).
• Experience with Mistral models and other machine learning frameworks.
• Strong understanding of machine learning algorithms and model evaluation techniques.
• Model monitoring and troubleshooting skills.
• Excellent problem-solving and analytical skills.
• Strong communication skills for technical and non-technical stakeholders.
• Collaborative teamwork in cross-functional teams.
• Strong knowledge on API Management and Integration using APIGEE API Management platform.
• Domino Datalab certification.
• MLOps Certification.
• Working knowledge of Scrum framework.

Our positions are open to people who have been recognized as disabled workers. T&S Group promotes diversity and equality in the workplace. All qualified M/F candidates are considered for employment on an equal basis.

Information :

• Company : Antaes
• Position : Machine Learning Engineer
• Location : Singapore
• Country : ID