Senior Machine Learning Engineer: Computer Vision & 3D

Role Overview

FitMatch is seeking a Senior Machine Learning Engineer to advance the computer vision and 3D reconstruction behind QuadraScan, starting with improving how we reconstruct human geometry from ordinary camera images, focusing on geometric accuracy, reliable measurements, and real-world performance. You'll own model development end to end, from data preparation and experimentation through evaluation and shipping, building on existing prototypes, datasets, and tools with real influence over our methods.

This is a hands-on senior IC role on a small team, reporting to the Head of Mobile Development. You'll align with them on objectives and trade-offs while independently driving ML implementation and technical decisions. We expect strong, evidence-backed recommendations and a track record of seeing work through to delivery.

Location:

Remote

Base salary:

$160,000–$200,000, depending on experience and work location

Responsibilities:

• Own model development for human reconstruction and related computer vision work, from data preparation and training through evaluation and production integration

• Select, adapt, and fine-tune pretrained models, modifying architectures or training objectives when a clear product need justifies it

• Design focused experiments with clear baselines, success criteria, and sensible time and compute limits

• Improve training data and capture coverage across synthetic and real imagery, maintaining reliable labels, dataset versioning, and train/eval subject separation

• Diagnose failures across the full pipeline, from capture quality and camera geometry to model predictions and reconstructed surfaces

• Evaluate geometric fidelity, regional errors, robustness, and failure rates, tying model metrics to scan and measurement quality

• Build maintainable training and inference code with reproducible experiments and practical regression checks

• Partner with mobile and backend engineers to deploy improvements, balancing accuracy, latency, memory, and cost

• Communicate findings clearly, including what the evidence supports, what remains uncertain, and the best next step

Qualifications:

• 5+ years of professional experience in ML, computer vision, or related engineering, with substantial hands-on model development

• Proven track record taking a computer vision model from experimentation into production and improving it based on real-world performance and failure cases

• Strong Python and PyTorch skills, including building training pipelines, modifying model components and losses, and diagnosing training issues