Remote Senior ML Engineer: Vision & 3D Reconstruction

FitMatch; Fort Lauderdale (FL); Remote; USD 160,000 - 200,000; Full time

Job summary

FitMatch seeks a Senior Machine Learning Engineer to advance QuadraScan's computer vision and 3D reconstruction. You will own model development end to end, from data prep to production, on a small team reporting to the Head of Mobile Development.

This remote, IC role emphasizes deep hands-on work, evidence-based decisions, and collaboration with mobile and backend engineers to balance accuracy, latency, and cost.

Qualifications

• 5+ years of professional ML/vision experience with hands-on model development.
• Proven track record deploying CV models to production based on real-world data.
• Strong Python and PyTorch skills for building training pipelines.
• Experience with geometric CV (depth estimation, camera calibration, 3D reconstruction).
• Solid software engineering fundamentals and ability to work independently.

Responsibilities

• Own model development for human reconstruction from data preparation to production integration.
• Select and fine-tune pretrained models, adjusting architectures when needed.
• Design experiments with clear baselines and success criteria.
• Improve training data and maintain dataset versioning.
• Diagnose failures across the pipeline from capture quality to model predictions.
• Evaluate geometry fidelity and robustness.
• Build maintainable training and inference code with reproducible experiments.
• Collaborate with mobile and backend engineers to deploy improvements.
• Communicate findings with clear evidence and recommendations.

Skills

Python

PyTorch

Computer Vision

3D Reconstruction

Data-driven decision making

Independent work

Job description

FitMatch seeks a Senior Machine Learning Engineer to advance QuadraScan's computer vision and 3D reconstruction. You will own model development end to end, from data prep to production, on a small team reporting to the Head of Mobile Development.

This remote, IC role emphasizes deep hands-on work, evidence-based decisions, and collaboration with mobile and backend engineers to balance accuracy, latency, and cost.