Machine Learning Engineer - III

We are looking for experienced Machine Learning Engineers with a background in software development and a deep enthusiasm for solving complex problems.

You will lead a dynamic team dedicated to designing and implementing a large language model framework to power diverse applications across Avalara.

Your responsibilities will span the entire development lifecycle, including conceptualization, prototyping and delivery of the LLM platform features.

You will have a blend of technical skills in the fields of AI & Machine Learning especially with LLMs and a deep-seated understanding of software development practices where you'll work with a team to ensure our systems are scalable, performant and accurate.

You will be reporting to Senior Manager, AI/ML.

This is a #LI-Remote role.

What Your Responsibilities Will Be We are looking for engineers who can think quick and have a background in implementation.

Your responsibilities will include:

• Build on top of the foundational framework for supporting Large Language Model Applications at Avalara
• Experience with LLMs - like GPT, Claude, LLama and other Bedrock models
• Leverage best practices in software development, including Continuous Integration/Continuous Deployment (CI/CD) along with appropriate functional and unit testing in place.
• Inspire creativity by researching and applying the latest technologies and methodologies in machine learning and software development.
• Write, review, and maintain high-quality code that meets industry standards.
• Lead code review sessions, ensuring good code quality and documentation.
• Mentor junior engineers, encouraging a culture of collaboration.
• Proficiency in developing and debugging software with a preference for Python, though familiarity with additional programming languages is valued and encouraged. What You'll Need to be Successful Bachelor's/master’s degree in computer science with 5+ years of industry experience in software development, along with experience building Machine Learning models and deploying them in production environments.
• Proficiency working in cloud computing environments (AWS, Azure, GCP), Machine Learning frameworks, and software development best practices.