Own and improve the end-to-end AI engine powering real-time voice drive-thru agents. Design conversational and order-taking logic, address turn-taking and noisy audio challenges, build evaluation infrastructure, and ensure accurate recommendations, substitutions, pricing, and POS integrations across restaurant brands. The role involves researching and deploying new AI techniques, training and productionizing machine learning models, and converting ambiguous quality issues into measurable improvements.
About the Role
At Arc, we are on a mission to amplify employees at local businesses using AI. With years of experience building and scaling commerce tools for businesses—from farmers markets and neighborhood coffee shops to global retailers, restaurant chains, and major sports venues—we know how to deliver mission-critical technology that integrates easily, delights customers, and works every time.
Voice drive-thru is our first product on that journey: an AI voice agent that takes real orders at the drive-thru speaker, in real time, integrating directly with a business's existing POS and hardware. Every order is a live conversation with a real customer — no undo button, no retry. Getting it right means building agents that are accurate under noisy audio, fast enough to feel natural, and tuned to actually grow revenue for the operators we serve, across brands with very different menus and POS systems.
As a Senior Applied AI Engineer, you'll own the end to end AI engine that powers our agents today. We have a pretty sophisticated AI stack that you'll be owning and continuously making improvements to it including researching and experimenting with new AI techniques, and rolling it out so that our agent is backed by the latest and greatest AI. This is a high-leverage, high-autonomy role for someone who wants to make a non-deterministic system demonstrably better every week, not just ship a prompt and hope.
What You'll Do
- Design and iterate on our conversational and order taking agent logic across multiple restaurant brands
- Own difficult problems like turn taking, background noise removal, side conversations, etc.
- Build and extend our evaluation infrastructure
- Work closely with POS and menu data to make sure agent behavior — recommendations, substitutions, pricing — stays correct as brands, menus, and integrations evolve in realtime
What We're Looking For
- 5+ years of professional software engineering experience, with significant hands-on experience training ML models from scratch and productionizing them at scale
- Strong Python skills and comfort working in a real backend codebase, not just notebooks
- Experience designing evaluation systems for non-deterministic outputs
- A track record of turning ambiguous quality problems into measurable metrics and concrete fixes
- Strong judgment about when to generalize agent behavior vs. specialize per brand/customer, and the communication skills to bring others along with your reasoning
- Bonus: experience with real-time/voice conversational agents, revenue or recommendation systems, or multi-tenant prompt/config management
Why Join Us
You'll have significant influence over both the product and the AI engineering culture at an early-stage company solving a genuinely hard, high-stakes problem: real-time AI that talks to real customers, in service of a mission to help local businesses run better. Voice drive-thru is just the beginning — your decisions will help shape what comes next.
Similar Jobs
Information Technology
Build scalable backend and distributed systems for agentic AI applications. Partner with Applied Scientists to productionize models, evaluation methods, and AI capabilities. Develop APIs, data flows, deployment and monitoring systems, and safe rollout processes for low-latency AI services. Improve reliability, scalability, performance, and cost efficiency while contributing to DialpadGPT and collaborating across research, product, and engineering teams.
Top Skills:
Agentic AiAPIsBackend ServicesCloud InfrastructureDistributed SystemsLarge Language ModelsModel ServingPythonService Observability
Blockchain • eCommerce • Fintech • Payments • Software • Financial Services • Cryptocurrency
Lead architecture and technical strategy for AI-driven product quality systems using LLMs and agents. Build scalable evaluation frameworks, detect regressions, generate insights, and drive cross-functional adoption while mentoring engineers and defining standards for trustworthy AI.
Top Skills:
AgentsAi InfrastructureEvaluation SystemsLlmsRetrieval Architectures
Retail • Analytics
Build, train, evaluate, and deploy production computer vision models (detection, segmentation, OCR, barcode decoding, visual search). Own dataset quality, tooling, model releases, inference exports, and monitoring. Collaborate cross-functionally to improve model performance, robustness, and deployment for retail robotics and edge environments.
Top Skills:
Barcode DecodingC++CudaCvatFiftyoneLabelboxLinuxOcrOnnxPythonPyTorchQuantizationRoboflowRosRos2TensorFlowTensorrt
What you need to know about the Chicago Tech Scene
With vibrant neighborhoods, great food and more affordable housing than either coast, Chicago might be the most liveable major tech hub. It is the birthplace of modern commodities and futures trading, a national hub for logistics and commerce, and home to the American Medical Association and the American Bar Association. This diverse blend of industry influences has helped Chicago emerge as a major player in verticals like fintech, biotechnology, legal tech, e-commerce and logistics technology. It’s also a major hiring center for tech companies on both coasts.
Key Facts About Chicago Tech
- Number of Tech Workers: 245,800; 5.2% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: McDonald’s, John Deere, Boeing, Morningstar
- Key Industries: Artificial intelligence, biotechnology, fintech, software, logistics technology
- Funding Landscape: $2.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Pritzker Group Venture Capital, Arch Venture Partners, MATH Venture Partners, Jump Capital, Hyde Park Venture Partners
- Research Centers and Universities: Northwestern University, University of Chicago, University of Illinois Urbana-Champaign, Illinois Institute of Technology, Argonne National Laboratory, Fermi National Accelerator Laboratory
