Software Engineer (Applied AI)

We are looking for a Staff level Software Engineer with experience working with the latest LLM's from OpenAI, Anthropic, Gemini, Mistral, Llama etc. 'and custom fine-tuned models i.e(Defog, Nous research) to help us advance our Manufacturing Systems and Operations. You will move fast prototyping ideas and experimenting with new approaches to solve existing problems better.

This role will work with and across multiple organizations and functional roles to develop solutions that not only end up in production, but have a significant impact. Some solutions will be stand alone while others will be built on top of existing systems through a deep collaboration. We want someone that has experience taking an idea from the whiteboard to production and then scale it. You are going to get to do that again here.

Description

The applications we build are used daily by the people at Apple that design our products along with those that figure out how to make them at scale. This includes; Manufacturing Design Engineers, Product Designers, Mechanical Engineers, Quality Engineers, Supply Chain Managers, along with our Suppliers. We work closely with them to design and architect the best solutions for the challenges faced when making the highest quality hardware products.

Minimum Qualifications

10+ years in a senior role working across the entire tech stack with a skilled team.

10+ years building robust HTTP APIs and backend services

Expert level grasp of at least 1 modern programming language: Go (preferred), Python, Java, etc.

Experience building solutions that leverage API's from the latest LLMs.

Preferred Qualifications

Experience with model pipeline and registry tools, detecting and preventing model drift, automating model monitoring, and ensuring model accuracy

Experience building robust evaluations for prompt optimization and tuning ML workflows

Experience with RAG and modern model in context learning techniques

Experience with SQL and database systems such as PostgreSQL

Experience with building ETL pipeline in data warehouse such as Snowflake

Manufacturing experience or exposure is a plus, but not required.