Role Summary

We are looking for a machine vision engineer to help build and scale our computational microscopy platform, developing models and systems that transform large-scale imaging data into actionable biological insight. You will work at the intersection of machine learning, software engineering, and scientific research to bring state-of-the-art models into reliable, production-ready pipelines. In this role, you will design, train, deploy, and maintain machine learning systems that support tasks such as cell segmentation, tracking, phenotyping, and image-based analysis at scale We are looking for an engineer who enjoys taking ML models from research to production and building the infrastructure that makes them robust, reproducible, and performant.

Key Responsibilities

• Design, train, and deploy machine learning models for microscopy and image-based biological data.
• Build scalable ML pipelines for data preprocessing, training, evaluation, and inference.

• Optimize model performance and throughput on modern hardware, including GPUs and multi-core CPUs.

• Collaborate with scientists and engineers to translate research prototypes into production systems.

• Integrate ML models into backend services, APIs, and data processing workflows.

• Monitor, benchmark, and improve model accuracy, robustness, and computational efficiency over time.

• Contribute to data representation, storage, and versioning strategies for large imaging datasets.

• Document model architectures, training procedures, and deployment workflows for internal and external use.

• Evaluate and adopt emerging ML techniques to improve scalability, accuracy, and interpretability.

Qualifications

Required:

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Electrical Engineering, or a related field (or equivalent experience).
• 2+ years of experience
• Strong proficiency in Python and experience with machine learning frameworks such as PyTorch, TensorFlow, ONNX, and TensorRT.
• Hands-on experience building and deploying ML models in production environments.
• Experience working with image-based or high-dimensional data; microscopy or medical imaging experience is a strong plus.
• Familiarity with model optimization techniques, including batching, quantization, or mixed-precision training.
• Experience with ML infrastructure, including experiment tracking, model versioning, and reproducible training workflows.
• Familiarity with cloud platforms and scalable compute environments (e.g., AWS, GCP, or Azure).
• Strong problem-solving skills, attention to detail, and scientific curiosity.
• Ability to communicate clearly and collaborate across disciplines.
• Experience with computer vision, segmentation, tracking, or representation learning.

Preferred:

• Master’s or Ph.D degree
• 5+ years of experience

Why You’ll Love Working Here

• Competitive salary and benefits, including equity options.
• Opportunity to work in a fast-paced, innovative environment.
• Exposure to various facets of business operations in a growing start-up.
• Professional development opportunities in a supportive setting.
• Access to cutting edge technology.

Equal Opportunity Statement

Ramona is an equal opportunity employer committed to diversity and inclusion in the workplace.

Interested? Send resume and cover letter to hr@ramonaoptics.com with subject “Machine VIsion Engineer Application” and brief answers to the following questions:

1. What is your experience with machine learning?
2. What is a project you have worked on outside of your academic studies and what excites you about it?
3. What skills do you hope to develop in working as a machine learning engineer at Ramona?

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