Staff Machine Learning Engineer — Shape Mental Health AI

Healy World; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Travel between NYC and London offices

Competitive compensation

Learning budget

Free lunch and coffee in office

Personal therapy covered

Job summary

Slingshot AI is hiring a Member of Technical Staff focused on Machine Learning. You will ship models, training infrastructure, harnesses, and evals end-to-end, building tech that makes Ash a differentiated mental health model and aims to impact billions of lives.

You will join a small, highly skilled team, acting as an owner and delivering value to users. We value how you think and build, not just background, and welcome engineers curious about ML to apply.

Qualifications

• 3+ years of engineering experience, owning systems other people rely on.
• Experience working with LLMs, ideally with fine-tuning, harness engineering, and evals
• Proficient in using agents to do your homework for you
• Driven by creating a world-class product with a world-class team, want to own what you build, and you're happy tearing down experiments and features as we learn
• Experience in a fast-paced startup, or the drive to thrive in one.
• Collaborative and direct. You enjoy working in person with a small team.

Responsibilities

• Ship models, training infrastructure, harnesses and evals end-to-end for Ash.
• Be a core member of a small, highly skilled team and own value delivery to users.
• Focus on a model-agnostic post-training engine and scalable performance improvements.
• Adopt a learning mindset and be willing to work with a wide toolset as needed.

Skills

Engineering

LLMs

Agents

Startup environment

Collaborative in person

Team ownership

Tools

Dart/Flutter

Kotlin

Next.js/TypeScript

Rust

gRPC

GCP

Job description

Slingshot AI is hiring a Member of Technical Staff focused on Machine Learning. You will ship models, training infrastructure, harnesses, and evals end-to-end, building tech that makes Ash a differentiated mental health model and aims to impact billions of lives.

You will join a small, highly skilled team, acting as an owner and delivering value to users. We value how you think and build, not just background, and welcome engineers curious about ML to apply.