AI Engineer

Mill is all about answering a simple question: how can we prevent waste? Less waste can save time, money, energy, maybe even our planet. And there’s no better place to start than food. Food waste is one of the most solvable climate problems facing us today. Plus, our trash really stinks. It’s gross, heavy, and our least favorite chore. At Mill we are striving to build a better environment for all, as we take on climate and kitchen change.

Role Description:

As an AI Engineer, you’ll help build and deploy high-quality AI models that set Mill’s products apart. AI models that provide significant value to customers and business partners. The core of your work will involve creating a valuable market differentiator for the company through intelligent predictions, with a strong focus on both traditional and generative AI, particularly in the field of computer vision.

You will help build out best practices and procedures and influence our growing company’s culture and team. An ideal candidate loves seeking out new problems and devising creative solutions, regardless of technology. Ideal candidates are also as excited about working on sustainability as we are!

Key Responsibilities

• Investigate and develop a range of AI models, from large-scale online systems to compact, edge-based equivalents.


• Collaborate closely with various teams, including firmware and data specialists, to uncover valuable insights from your models.


• Work with engineering teams to deploy these models and establish the necessary metrics to effectively monitor their performance across a vast network of thousands of product installations.

Minimum Qualifications

• Bachelor’s or Master’s degree in Computer Science or a related quantitative field (e.g., Data Science, Mathematics, Economics, Physics) with relevant industry experience.


• 5+ years of industry experience with Python.


• Proficiency in common AI/ML frameworks like PyTorch and HuggingFace Transformers.


• Experience with both generative AI (LLMs, SLMs, and VLMs) and traditional computer vision models (YOLO, MobileNet, EfficientNet).


• Experience with prompt-tuning methodologies (logits sampling, RAG) and model fine-tuning techniques (including LORA-based methods for transformers).


• Skill in developing performance benchmarks and establishing best practices for model deployment and monitoring.


• Experience with cloud-scale model hosting services, such as AWS Bedrock.

Preferred Qualifications

• Experience with edge AI/ML frameworks and runtimes (QNN, llama.cpp).


• Proficiency in C/C++ or other languages suitable for edge devices.


• Experience with agentic frameworks (Autogen, SWARM) and agentic RAG.


• Knowledge of advanced post-training techniques like model distillation or quantization.


• Experience with reinforcement learning for transformers.


• Cloud-based AI orchestration (preferably in AWS).

The estimated base salary range for this position is $200k to $250k, which does not include the value of benefits or a potential equity grant. A wide range of factors are considered in making compensation decisions, including but not limited to skill sets, market conditions, experience and training, licensure and certifications, and business and organizational needs. At Mill, it is not typical for an individual to be hired at or near the top of the range for their role.