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[Remote] Machine Learning Engineer V

Work from home Full-time role Hiring

Note: The job is a remote job and is open to candidates in USA. Avalara is accelerating an AI-first transformation, and they are seeking a Machine Learning Engineer V to help build and scale the Avalara Avi Agent. This role will focus on developing reliable, production-grade systems to improve automation and customer outcomes while establishing best practices for agentic applications.

Responsibilities

  • Design, build, and operate foundational agentic platform capabilities that enable Aviator, AAA, and other Avalara agentic experiences to move from prototype to production
  • Develop scalable LLM application frameworks, orchestration patterns, tool integrations, and agent workflows that support enterprise-grade reliability, observability, security, and maintainability
  • Create and improve evaluation methods for agentic outcomes, including quality, accuracy, latency, cost, safety, and task-completion effectiveness
  • Translate ambiguous business and product needs into technical designs, prototypes, production features, and measurable engineering outcomes
  • Apply modern software engineering practices, including CI/CD, automated testing, code review, documentation, and operational readiness, to ensure high-quality delivery
  • Partner with product, engineering, security, data, and business stakeholders to ensure agentic capabilities solve meaningful customer and operational problems
  • Research, assess, and responsibly apply emerging AI technologies, including LLMs, model-context protocols, agent-to-agent patterns, retrieval, evaluation, and automation techniques
  • Document reusable patterns and implementation guidance that help Avalara engineers and software agents build consistently, safely, and efficiently
  • Mentor engineers and raise the technical bar through design reviews, code reviews, coaching, and examples of high-ownership execution
  • Strengthen the operational robustness of mature high-availability systems while introducing new AI capabilities without compromising customer trust or production stability

Skills

  • B.S. in Computer Science, Engineering, or a closely related technical field
  • 8+ years of relevant professional experience building, deploying, and operating production software systems, with strong preference for Python experience
  • Hands-on experience building LLM applications, agentic systems, or AI-enabled workflows in production or production-like environments
  • Experience with LLMs such as GPT, Claude, Llama, or similar models, including practical understanding of prompting, orchestration, evaluation, and reliability considerations
  • Experience with enterprise-scale software design, distributed systems, data structures, design patterns, and high-availability system operations
  • Experience working in cloud computing environments such as AWS, Azure, or GCP
  • Applied familiarity with modern agentic integration patterns and protocols, such as MCP, A2A, tool use, retrieval, and multi-agent orchestration
  • Demonstrated ability to use AI to improve measurable outcomes, such as speed, quality, automation, insight, customer experience, or scale
  • Strong communication, documentation, mentoring, and cross-functional collaboration skills

Benefits

  • Paid time off
  • Paid parental leave
  • Many Avalara employees are eligible for bonuses
  • Private medical insurance
  • Life insurance
  • Disability insurance
  • 8 employee-run resource groups, each with senior leadership and exec sponsorship

Company Overview

  • Avalara is a cloud-based platform that provides tax compliance software and automated solutions. It was founded in 2004, and is headquartered in Seattle, Washington, USA, with a workforce of 5001-10000 employees. Its website is http://www.avalara.com.
  • Company H1B Sponsorship

  • Avalara has a track record of offering H1B sponsorships, with 10 in 2026, 26 in 2025, 33 in 2024, 34 in 2023, 37 in 2022, 39 in 2021, 26 in 2020. Please note that this does not guarantee sponsorship for this specific role.
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