Premera Blue Cross

AI Engineer II

Premera Blue Cross

full-time

Posted on:

Origin:  • 🇺🇸 United States

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Salary

💰 $95,600 - $162,500 per year

Job Level

Junior

Tech Stack

CaffeCloudMicroservicesNumpyPandasPythonPyTorchScikit-LearnTensorflow

About the role

  • Develop components of larger AI systems and frameworks for AI applications and products.
  • Assist in the development of prototypes and minimum viable AI/ML products before contributing substantial resources.
  • Assist in the implementation of large complex cloud-based AI systems by focusing on individual components.
  • Support senior AI Engineers in implementing data pipelines that underly large complex AI systems.
  • Assist in implementing low latency APIs within a larger microservices architecture for powering AI models and services.
  • Assist in the monitoring of deployed models and participate in a reporting process that ensures optimal model performance.
  • Actively participate in a team that exercises principled, agile-like development practices.
  • Create and maintain thorough documentation that is consistent with team procedures, corporate policies, and expectations.
  • Follow peer review procedures for all assigned work.
  • Keep abreast of new tools and concepts through reading documentation or literature and actively practice skills development.
  • This is a telecommuter position, working from home.

Requirements

  • Bachelor's Degree in Computer Science, Statistics, Mathematics, or a related field, or 2+ years of experience in a related, professional IT/analytics position.
  • Minimum of 1 year of industry experience in developing, deploying, and maintaining AI or ML systems.
  • At least 2 years of experience in developing deep learning models using TensorFlow, PyTorch, MLX, JAX, or other modern deep learning frameworks.
  • Previous experience with older libraries like Theano, or Caffe is also accepted. (May substitute with demonstrable graduate level education, research experience, or capstone projects).
  • Knowledge of ethical AI principles and demonstrated experience in implementing or assessing explainable AI and fairness measures in at least one project.
  • Be able to apply basic prompt engineering techniques in practice as demonstrated by certification or completion of one or more projects. As part of this, familiarity with tools like LangChain or Chainlit for generating and refining prompts is essential. Familiar with advanced concepts such as Chain of Thought (CoT) Prompting and Self Consistency, and the role of in-context learning in prompt engineering.
  • Completed at least one RAG application with tools or technologies like LangChain or Llama Index.
  • Participation in at least one multi-member team practicing Agile methodologies.
  • Knowledge, Skills, and Abilities Familiarity with deep learning architectures such as CNNs, transformers, GANs, LSTMs, GNNs, Autoencoders, Diffusion Models, and Neural Ordinary Differential Equations (NODEs).
  • Proficiency in debugging AI systems and enhancing performance through hyperparameter tuning and similar techniques.
  • Experiences productionizing models by constructing scalable data pipelines, low-latency services, and robust monitoring.
  • Familiarity with software design patterns, microservices, distributed computing, container orchestration, and other relevant architectures.
  • Exposure to software engineering as well as building secure, stable software systems at scale.
  • Proficiency in developing and optimizing ML solutions using languages like Python and libraries such as NumPy, Pandas, Matplotlib and scikit-learn.
  • Familiarity working with traditional ML lifecycles.
  • Familiarity with ethical AI practices including explainable AI, fairness, and mitigation of bias/hallucinations.
  • Solid communication and collaboration skills.
  • Familiarity working within Agile-like teams and environments.