AI/ML Engineers for Scalable Platforms
Publicada el 2026-07-21
Descripción de la oferta
I’m expanding our engineering group to tackle several green-field products that blend full-stack web work with a major AI initiative. My most urgent need is someone who lives and breathes machine learning—specifically model training and optimisation—and is comfortable doing it in Python. You’ll take ownership of the entire training workflow: building data pipelines, crafting efficient training loops, fine-tuning models, and squeezing every drop of performance out of our GPU clusters on AWS. Because the broader team also works in Rust micro-services and Ruby on Rails APIs, an appreciation for end-to-end software delivery is important; your models will eventually power customer-facing features served from those back-ends. Core responsibilities • Design and implement reproducible ML pipelines in Python. • Optimise training workflows for speed, cost, and accuracy. • Evaluate, version, and monitor models once they’re in production. • Collaborate with the cloud and full-stack teams to expose prediction services via robust APIs. Acceptance criteria • A functioning training pipeline (ideally using PyTorch or TensorFlow) that runs end-to-end on our AWS account. • Clear documentation and unit tests. • Demonstrable improvement over baseline benchmarks we will provide. If you also enjoy Rust, Rails, or architecting large-scale cloud infrastructures, there will be plenty of space to apply that expertise as the product grows. When you submit a proposal, please include: – A brief example of a recent model-training project, including dataset size and achieved metrics. – Your favourite optimisation technique and why it matters. – Any AWS services you’ve leveraged for ML workloads. I’m excited to see how your skills can help push our AI projects—and the entire platform—to the next level.
Skills
Fuente original: freelancer