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Apple Sales - Machine Learning Engineer AIOps Singapore 724694452
07.04.2025
You will collaborate with multi-functional teams of business SMEs, engineers, data scientists, designers, and researchers. This role is exceptionally technical, and will require you to actively engage in all aspects of the work, from conceptualization and theoretical considerations to design, coding, and implementation.
In this role, you will focus on the following key areas:Model Management: Oversee the deployment, maintenance, and scaling of LLM, and services within our consumer-facing products.CI/CD: Build and maintain CI/CD pipelines to automate model train/test/deployment and scaling.Continuous Monitoring: Build Dashboard and Regularly track model performance, ensuring consistent accuracy and reliability for consumers. Set up alerts and manage the type of monitoring needed.Feedback Integration: Develop strategies for collecting user feedback and refining the model for better alignment with consumer needs.Bias Mitigation: Proactively address and reduce potential biases in model predictions, ensuring our products are inclusive and fair.Infrastructure Management: Design and implement efficient data pipelines to support large language model training and inferenceDocumentation: Maintain comprehensive documentation covering model versions, deployment protocols, and performance metrics.Research & Development: Stay updated with the latest trends in large language models and MLOps, ensuring our consumer products remain at the forefront of innovation.
- M.S. in related field with 3+ years experience applying AIOps machine learning engineer to real business problems.
- Language Model Expertise: Demonstrated experience working with large language models, such as OpenAI's GPT series or similar.
- MLOps Skills: Solid background in Automating ML pipeline, including the training, testing, deployment, monitoring, and scaling of AI models.
- Technical Toolkit: Proficiency in PyTorch, TensorFlow, Transformers, Kubernetes, Docker, LangChain, vectorDB and cloud platforms like AWS, GCP, or Azure, and Monitoring tool like Grafana, and CI/CD like airflow, gitlab, and Big Data management like Spark, Kafka.
- Product-Centric Mindset: Proven track record of integrating AI models into consumer products, enhancing functionality, and user experience.
- Communication Prowess: Excellent communication skills, with the ability to liaise between technical and non-technical teams.
- Collaborative Spirit: Experience in cross-functional teams, ensuring seamless product development.
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