MLOps Architect

5 days ago

Singapore beBeeMachineLearningEngineer Full time

Job Title: Senior MLOps Engineer ">

Are you looking for a challenging role that combines machine learning with engineering principles? We are seeking a highly skilled MLOps Engineer to join our team. As an MLOps Engineer, you will be responsible for designing, developing, and deploying AI models into production.

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Our ideal candidate will have a strong background in computer science, with a minimum of 3 years of experience in machine learning and operations. You should be proficient in programming languages such as Python, and have experience with ML frameworks like TensorFlow, Keras, and PyTorch.

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You will work closely with engineers and domain experts to develop and maintain code, documentation, testing, and deployment frameworks, tools, and infrastructure. This includes creating and maintaining pipelines for machine learning model training, data management, and model deployment.

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Key responsibilities include:

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  • Create and maintain code, documentation, testing, and deployment frameworks, tools, and infrastructure.
  • Develop environments for building, testing, tracking production AI models and data across data pipelines used in primary and secondary genomic analysis.
  • Be a technical expert to develop AI models within a consistent ML environment, automate training and data/model management.
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Requirements:

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  • Bachelor's degree in Computer Science or equivalent experience.
  • Minimum 3 years of experience in machine learning and operations, ideally in a hands-on MLOps role.
  • Experience deploying APIs and packages.
  • Experience with ML ops platforms (MLFlow, W&B; Kubernetes, Docker, dask, Ray).
  • Experience with ML frameworks (Tensorflow, keras, Pytorch, xgboost, sklearn).
  • Strong Python coding skills - experience with unit testing, code reviews, version control.
  • Alternatively, you could be a DevOps Engineer with ML experience, a Bioinformatics Engineer with AI/ML ops related experience, or an ML Engineer with DevOps experience.
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Benefits:

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  • Hybrid working arrangement - 2 days WFH.
  • Working hours 8am to 5pm. Can end work early and have more personal time.
  • Occasional US calls.
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To apply online, please use the 'apply' function. Alternatively, you may contact Stella at EA: 94C3609/R

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Keywords: MachineLearningEngineer

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