BayOne Solutions - Sunnyvale, CA

posted 2 months ago

Full-time - Mid Level
Sunnyvale, CA
Professional, Scientific, and Technical Services

About the position

The Cortex team is at the forefront of developing an advanced A.I. platform that aims to deliver the world's best intelligent personal assistants to customers. These assistants are designed to be accessible through natural voice commands, text messages, and rich UI interactions, creating a seamless multi-modal experience. The team believes that conversations serve as a natural and powerful interface for technology, enhancing customer experiences both online and in-store. The focus is on building and designing the next generation of Natural Language Understanding (NLU) services that can be easily integrated by other teams to create rich user experiences, ranging from voice and text shopping assistants to customer care channels and mobile applications. As a Senior AI/ML Engineer, you will be responsible for developing, testing, and refining prompts for various applications, including text generation, question answering, data classification, and synthetic training data generation. You will also develop and maintain principled regression test suites to ensure prompt compliance at scale for mission-critical applications. Analyzing and iterating on prompts based on performance metrics, user feedback, and new product requirements will be a key part of your role. Collaboration with legal, product, and data science teams will be essential to align prompts with overall company goals and compliance standards. You will need to navigate the prompt characteristics of multiple model architectures, including GPT, Llama, and Gemini, as well as different versions of these models. A creative approach to assessing safety exposure and strengthening compliance characteristics of prompts will be necessary. Continuous research and education in the rapidly evolving AI field will be expected, as you will have the opportunity to make a significant impact on the design, architecture, and implementation of a mission-critical product that is used daily by customers.

Responsibilities

  • Develop, test, and refine prompts for various applications including text generation, question answering, data classification, and synthetic training data generation.
  • Develop and maintain principled regression test suites to ensure prompt compliance at scale for mission-critical applications.
  • Analyze and iterate on prompts based on performance metrics, user feedback, and new product requirements.
  • Collaborate with legal, product, and data science teams to align prompts with company goals and compliance standards.
  • Navigate prompt characteristics of multiple model architectures and versions.
  • Assess safety exposure of prompts and strengthen compliance characteristics.
  • Engage in continuous research and education on the evolving AI field and large model properties.

Requirements

  • Solid data skills and sound computer-science fundamentals.
  • Strong programming experience, particularly in Python.
  • Experience with at least one relational database technology such as MySQL, PostgreSQL, Oracle, or MS SQL.
  • Deep hands-on technical expertise in development, preferably full-stack.
  • Good data-processing and testing fundamentals.
  • Ability to take a project from scoping requirements through to actual launch.
  • Ability to deal with ambiguous or undefined problems.
  • Continuous drive to explore, improve, enhance, automate, and optimize systems and tools.
  • Capacity to apply scientific analysis and mathematical modeling techniques to predict, measure, and evaluate design consequences and platform success.
  • Excellent oral and written communication skills.
  • Bachelor's degree or certification in Computer Science, Engineering, Mathematics, or a related field.

Nice-to-haves

  • Proficient in multiple models and AI-related tools.
  • Exposure to cloud infrastructure such as Open Stack, Azure, Google Cloud Platform, or AWS.
  • Experience with infrastructure management technologies like Docker and Kubernetes.
  • Focus on scalability, latency, performance robustness, and cost trade-offs in cloud-based environments.
  • Hands-on expertise in a range of technologies from front-end user interfaces to back-end systems.
  • Familiarity with Machine Learning concepts and processes.
  • Masters or PhD in Computer Science, Physics, Engineering, Math, or equivalent.
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