Machine Learning Engineer IV

What You'll Do

AI is transforming how Avalara builds products, automates compliance workflows, and delivers intelligent experiences at scale. As we advance toward our mission of being part of every transaction in the world, our AI and ML teams are building applied AI systems that can understand complex text, documents, products, and compliance data. In this role, reporting to the [Sr Manager, Machine Learning, you will join our AI and ML team to help turn cutting-edge AI techniques into reliable, secure, and scalable systems. You will play a key part in improving automation quality, product capabilities, and developer velocity by building intelligent systems that move beyond prototypes into real-world production impact. If you want to work on production-grade AI systems that raise the engineering bar across the company, Avalara is an amazing place to build your career.

What Your Responsibilities Will Be

• Design, build, and improve production ML systems for classification, document understanding, retrieval, and AI-powered automation.
• Fine-tune and evaluate transformer-based models, small language models, and other ML approaches for practical business use cases.
• Build and optimize real-time inference services, batch-processing pipelines, APIs, and model-serving workflows.
• Develop evaluation frameworks to measure model quality, accuracy, latency, reliability, cost, and failure modes.
• Contribute to GenAI platform capabilities such as RAG, embeddings, prompt systems, document ingestion, and agent workflows.
• Productionize ML and LLM-powered services with strong reliability, observability, security, and cost controls.
• Mentor junior engineers and help raise team capability in applied AI and production ML practices.
• Raise the technical quality and production maturity of AI and ML systems by bringing rigor to how models are evaluated, monitored, and improved.

What Youll Need To Be Successful

• B.E. in Computer Science, Engineering, or a related technical field.
• 6+ years of experience in machine learning engineering, applied ML, NLP, information retrieval, GenAI, or production AI systems.
• Strong software engineering skills in Python and experience building backend services, APIs, or distributed systems.
• Experience building, evaluating, and deploying ML models in production environments.
• Experience with modern ML or AI techniques such as text classification, transformers, embeddings, RAG, LLMs, SLMs, or document AI.
• Familiarity with model serving, batch and real-time inference, monitoring, observability, and cloud-native deployment.
• Ability to work across ambiguous business and technical problems and convert them into measurable ML improvements.
• Strong collaboration and communication skills across engineering, product, and domain stakeholders.