Job Description & How to Apply Below
About Meta Optima: Join Meta Optima to make a difference in the lives of millions as we revolutionize the dermatology industry with software, hardware and AI for faster, more effective, and affordable care. Meta Optima is full of passionate, innovative people who thrive on working together as a team to build smart, life‑saving technologies for medical professionals and their patients. Our casual, open-office culture welcomes fresh ideas from the minds of doers.
Join us to add your voice to our vision while working with a cool group of people set on making their mark on the world. We take pride in what we’ve accomplished together, and can’t wait to see how you’ll help us grow.
Job Summary:
As a Machine Learning Engineer, you will join a small, high-impact R&D team and own the full ML lifecycle — from research and rapid prototyping through data pipelines, model training, and cloud deployment. Your work will directly shape clinical‑grade computer vision systems that help dermatologists and their patients around the world.
Responsibilities Understand business problems and brainstorm AI solutions collaboratively with the team.
Work across all stages of the ML pipeline — from data cleaning and acquisition through implementation and deployment.
Rapidly prototype research ideas and estimate the effort required to develop an MVP.
Develop tooling to clean, label, and manage medical image datasets.
Analyze MVP performance to determine how to scale solutions for full cloud deployment on AWS or GCP.
Optimize models for inference performance.
Compile and present research findings in a clear and understandable way for both technical and non‑technical stakeholders.
Qualifications (must‑have) Master’s or PhD degree in Computer Science or equivalent work experience
2+ years of non‑internship hands‑on experience in machine learning.
Strong proficiency in Python and PyTorch.
Computer vision experience (classical and deep learning).
Experience deploying ML models at scale on AWS or GCP.
Familiarity with containerization tools such as Docker.
Solid understanding of CI/CD practices for ML systems.
Comfortable working with and reviewing medical images.
Proficient with ML/scientific computing libraries (scikit‑learn, scipy, numpy).
Able to determine and apply the correct evaluation metrics for model performance assessment.
Self‑starter with strong communication, documentation, and presentation skills.
Able to work effectively in a fast‑paced startup environment.
Preferred Qualifications
Experience with 3D vision and/or multiview geometry.
Enjoys reading and keeping up with academic research papers.
Why Join Us You’ll play a pivotal role in advancing next‑generation imaging technology for dermatology, helping transform how skin is captured, reconstructed, and analyzed worldwide.
If you’re excited to turn cutting‑edge machine learning research into clinical‑grade imaging technology, we’d love to hear from you.
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