Senior AI Machine Learning Engineer

Get to Know Us

This role is specifically for an AI-powered Invoice-to-Cash solution, a platform that uses intelligent automation to help companies collect cash faster, unlock working capital, and improve efficiency in accounts receivable processes.

Make Your Mark

As an AI Engineer, you will develop and deploy innovative applications using Large Language Models (LLMs) and foundation models. The role requires a deep understanding of AI Engineering and practical experience deploying GenAI solutions at scale.

Benefits

• Retirement plan
• Life and disability coverage
• Healthcare
• Wellness benefit
• Business travel accident insurance covering medical expenses, life, and accidental injury during business travel
• Employee assistance program
• Annual performance bonus of 7–15%, depending on level and performance
• Restricted Stock Units (RSUs) may be offered to eligible employees
• Reduced tax-deductible expenses: 84% of developers' time is recognized as creative work

You'll Get To

• Design, build, and deploy production-grade applications that use foundation models to deliver insights and efficiency for Finance and Accounting teams.
• Develop robust evaluation methodologies for open-ended AI systems, including AI-as-a-judge approaches, to ensure accuracy and reliability.
• Apply prompt engineering, Retrieval-Augmented Generation (RAG), and fine-tuning to tailor foundation models to financial use cases.
• Create and manage datasets for model training and fine-tuning, ensuring data quality and relevance.
• Build and deploy AI agents that automate complex financial workflows and interact with tools and systems.
• Optimize AI applications to reduce latency and cost.
• Collaborate with cross-functional teams to implement AI-powered solutions for office-of-the-CFO challenges.

What You'll Bring

Technical/Specialized Knowledge, Skills, and Abilities:

• Proven experience developing and deploying applications using foundation models, such as GPT-4o/o3, Claude Opus 4.x/Sonnet 4.x, or Llama 3.x.
• Strong understanding of AI Engineering as distinct from traditional Machine Learning Engineering.
• Hands-on prompt-engineering experience, including few-shot and zero-shot learning and defensive prompt design.
• Practical knowledge of RAG architecture for knowledge-intensive applications.
• Experience fine-tuning LLMs and understanding when to use fine-tuning versus RAG.
• Experience building and evaluating AI agents for complex, multi-step tasks.
• Familiarity with foundation-model evaluation challenges and experience designing and implementing evaluation pipelines.
• Proficiency in Python or C# and experience with frameworks and libraries such as Hugging Face Transformers, LangChain, LangGraph, and PyTorch.

We're Even More Excited If You Have

• Experience designing or operating AgenticOS patterns, including memory management, tool registries, agent lifecycle orchestration, and inter-agent communication.
• Knowledge of inference optimization techniques, including quantization, to improve latency and cost.
• Expertise in multimodal generative models across text, image, and audio.
• Deep dataset-engineering knowledge, including data curation, augmentation, and synthesis.
• Experience designing end-to-end Generative AI systems from data ingestion and model orchestration through scalable deployment and continuous monitoring.
• Understanding of LLMOps principles and experience managing the production lifecycle of LLMs.
• Experience with Model Composition (MCP) techniques combining specialized models or AI agents.
• Knowledge of Responsible AI and experience implementing guardrails, safety filters, and ethical considerations for generative models.
• Familiarity with the financial domain and applying AI in a regulated industry.

Work Model

• Hybrid work model: local candidates work in the office at least 3 days per week.

Additional Offer Highlights

• Professional development seminars and inclusive affinity groups.
• Equal opportunity employer.
• Workplace combining virtual and in-person interactions to support collaboration.