AIOps Machine Learning Engineer Position

2 weeks ago

Singapore beBeeArtificial Full time $120,000 - $180,000
Machine Learning Engineer, AIOps Role

Imagine what you could accomplish by working with large language models and generative AI to create innovative products for global audiences.

Job Overview

We are seeking a highly skilled and experienced AIOps Machine Learning Engineer to join our team of talented engineers and researchers. This role will involve working on exciting technologies for future products and collaborating with multi-functional teams to discover and build solutions to previously-unsolved challenges.

Key Responsibilities
  • Oversee the deployment, maintenance, and scaling of large language models and services within our consumer-facing products.
  • Build and maintain CI/CD pipelines to automate model train/test/deployment and scaling.
  • Partner with product developers, UX designers, and data scientists to ensure seamless integration of language models into our products.
  • Continuously monitor model performance, ensuring consistent accuracy and reliability for consumers.
  • Develop strategies for collecting user feedback and refining the model for better alignment with consumer needs.
  • Proactively address and reduce potential biases in model predictions, ensuring our products are inclusive and fair.
  • Design and implement efficient data pipelines to support large language model training and inference.
  • Maintain comprehensive documentation covering model versions, deployment protocols, and performance metrics.
  • Stay updated with the latest trends in large language models and MLOps, ensuring our consumer products remain at the forefront of innovation.
Qualifications
  • Master's degree in a related field with 3+ years of 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.
Preferred Qualifications
  • 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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