Senior Computer Vision Engineer

Epia Neuro; Alameda (CA); On-site; USD 170,000 - 210,000; Full time

Benefits offered by this job

Competitive base salary with equity

Healthcare coverage for you and depend

Generous vacation policy

Paid parental leave

Work from Alameda waterfront office

Job summary

Epia Neuro is seeking a Senior Computer Vision Engineer to lead perception model development and.cpp accelerate model deployment for wearable medical hardware. You will work closely with R&D scientists to take models from concept to production-ready runtime, balancing latency, power, and accuracy in a regulated environment.

The role is based in Alameda, CA, with 2–3 days/week on-site. You will guide cross-functional teams across Software, Firmware, Hardware, and Robotics to deliver clinically

Qualifications

• BS degree or higher in a relevant technical field and 7+ years of industry CV/ML experience.
• Hands-on experience taking ML models from research to deployed production systems.
• Proficiency with real-time/edge inference and device-level optimization.

Responsibilities

• Develop CV models from concept to prototype and lead productization.
• Design data collection, annotation, and evaluation pipelines tied to clinical use.
• Optimize models for real-time latency and power on wearable hardware.
• Own integration of CV/ML models into medical device software stacks.

Skills

7+ years of CV/ML experience

Hands-on model development

Real-time/edge inference

Python programming

C++ for inference runtime

Cross-functional collaboration

Model optimization (quantization/prune

Education

Bachelor’s degree in Computer Science, Electrical Engineering, Robotics, or related field

PhD in Computer Vision, ML, Robotics, or related discipline

Tools

PyTorch

ONNX

TensorRT

TFLite

Job description

About Us

Epia Neuro is a neural technology company developing intent-driven systems that restore function and independence for people living with neurological conditions. Our platform integrates implantable neural interfaces, adaptive algorithms, and assistive devices to translate neural intent into real‑world action. Our initial focus is stroke‑related motor impairment, with planned expansion into cognitive decline and other neurological disorders.

The Role

We’re looking for a Senior Computer Vision Engineer with deep computer vision (CV) and machine learning (ML) expertise, a hands‑on approach, and a track record of taking models into production. You’ll be the first dedicated computer vision engineer on the program. Partnering with our R&D scientists, you’ll help shape vision models from concept, then lead their productization from validated prototype to a real‑time inference runtime on wearable hardware, ready for clinical study. You’ll report to the Senior Director of Software.

Location

This role is based out of the San Francisco Bay Area and is expected to work on site from our Alameda headquarters 2‑3 days a week.

How We Work

• We are intentional. We prioritize and are thoughtful about how we use others’ time.
• We care for others. We prioritize safety both for patients and one another.
• We own outcomes, not just tasks. Our work demands the highest standards because it impacts real patients and real lives.
• Humility is a strength. We are honest about what we know and what we don’t know. Getting it right matters more than being right.

What You’ll Do

Perception Model Development

• Collaborate with R&D scientists to develop computer vision models, taking them from concept through prototype.
• Bring computer vision and machine learning depth to the research effort, including model design, training, and evaluation.
• Help define data collection, annotation, and evaluation protocols, and establish performance criteria tied to clinical use.
• Build prototype models and pipelines that are ready to carry into productization.

Productization, Integration & Deployment

• Lead and own productization of the computer vision models, taking validated prototypes to a deployable inference runtime that meets real‑time latency and power budgets on wearable and edge hardware.
• Optimize model performance, including quantization, pruning, and distillation.
• Profile latency and resource use across the inference path.
• Own integration of the models into the broader medical device product, working with Software, Firmware, Hardware, and Robotics teams.
• Define and execute benchtop and system‑level validation to characterize accuracy, robustness, and performance to clinical study readiness.
• Lead debugging and root‑cause analysis across the machine learning, firmware, and controls boundaries.
• Drive technical decisions for system reliability and performance across prototype and pre‑production builds.

Technical Leadership & Cross‑Functional Execution

• Serve as the technical lead for computer vision engineering across the program.
• Help establish machine learning engineering processes, documentation standards, and test methodologies within our regulated software lifecycle.
• Partner with cross‑functional stakeholders to define technical requirements, integration milestones, and validation criteria.
• Support vendor selection, component evaluation, and design trade‑off analysis for cameras, compute, and computer vision/machine learning tooling.
• Contribute to long‑term computer vision/machine learning platform strategy.

Qualifications

• Bachelor’s degree in Computer Science, Electrical Engineering, Robotics, Machine Learning, or related field.
• 7+ years of industry experience developing and deploying computer vision or machine learning systems.
• Strong expertise in computer vision, including object detection, segmentation, and pose or keypoint estimation, with hands‑on model training, evaluation, and dataset curation.
• Demonstrated experience taking machine learning models from research prototype to a deployed, production system working under real constraints.
• Hands‑on experience with real‑time and edge inference, including model optimization, latency and resource profiling, and deployment to embedded or mobile targets.
• Production‑quality Python, plus proficiency in C++ or embedded development for the inference runtime.
• Experience with modern machine learning frameworks and deployment toolchains (e.g., PyTorch; ONNX, TensorRT, TFLite, or similar edge toolchains).
• Excellent communication and cross‑functional collaboration skills, with the ability to drive technical initiatives across teams.

Preferred Qualifications

• PhD in Computer Vision, Machine Learning, Robotics, or related discipline.
• Real‑time computer vision for robotics, wearables, or other human‑interactive systems.
• Sensor fusion or visual servoing experience.
• On‑device or mobile machine learning, including Android.
• Familiarity with safety‑critical or regulated systems, such as medical devices (IEC 62304, ISO 13485, design controls) or other rigorous V&V environments.
• Background or interest in rehabilitation, assistive technology, or neurotechnology.

Physical Requirements

• Ability to work on site in a lab environment, including participating in hands‑on data collection and bench testing with prototype hardware. Requires manual dexterity for handling devices, some standing during test and integration sessions, and the ability to safely operate lab equipment.

Benefits

• Competitive base salary with equity
• 100% of healthcare coverage for you and your dependents
• Generous vacation policy
• Paid parental leave
• Work from our beautiful waterfront office in Alameda, CA, with access to collaborative spaces and labs.

Compensation Range: $170K - $210K