This position is posted by Jobgether on behalf of BrightAI. We are currently looking for a Staff Computer Vision/AI Engineer in the United States.
This senior engineering role offers an exciting opportunity to lead the development of state-of-the-art computer vision and AI systems that power real-time decision-making across diverse devices and services. You will work on cutting-edge research and production-level machine learning models focused on visual, spatial, and temporal data. Collaborating closely with cross-functional teams, you will help architect scalable, robust AI platforms that transform how physical infrastructure industries operate. This role suits a highly experienced engineer passionate about innovation, complex problem solving, and deploying impactful AI solutions at scale.
Accountabilities:
- Lead the end-to-end lifecycle of computer vision and machine learning models, from data collection and labeling through production deployment and monitoring.
- Research, design, and implement deep learning models for tasks such as detection, segmentation, classification, tracking, and real-time inference.
- Drive projects from prototyping to production, aligning with product goals and platform requirements.
- Collaborate with product, hardware, and cloud teams to deliver integrated, intelligent AI features.
- Architect scalable, reliable AI systems that solve complex real-world challenges.
- Prioritize and manage multiple initiatives to optimize model performance, reliability, and compliance.
- Stay abreast of the latest AI/ML advancements and incorporate relevant innovations into the product roadmap.
Requirements
- 7+ years of professional experience in computer vision and machine learning with deep expertise in applied deep learning.
- Proven track record delivering production-grade AI/ML solutions in fast-paced environments.
- Comprehensive experience across the ML development lifecycle, including data curation, model training, evaluation, optimization, and deployment.
- Proficiency in deep learning frameworks such as PyTorch or TensorFlow and strong programming skills in Python; C++ is a plus.
- Hands-on experience with CNNs, YOLO, Vision Transformers, model compression techniques, and real-time inference optimization.
- Experience deploying models on cloud platforms (AWS, GCP, Azure) and edge devices using tools like TensorRT, ONNX, or TFLite.
- Strong analytical and problem-solving skills with the ability to translate ambiguity into actionable solutions.
- Excellent teamwork and communication skills to work cross-functionally with software, hardware, and product teams.
- PhD in Electrical Engineering, Computer Science, or related field, with demonstrated research excellence in computer vision.
Benefits
- Competitive salary and equity compensation package.
- Flexible remote work environment.
- Comprehensive health, dental, and vision insurance plans.
- Professional development opportunities and conference support.
- Supportive and collaborative company culture focused on innovation and growth.
- Modern equipment and tools to support your work.
Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.
When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly.
🔍 Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience and achievements.
📊 It compares your profile to the job’s core requirements and past success factors to determine your match score.
🎯 Based on this analysis, we automatically shortlist the 3 candidates with the highest match to the role.
🧠 When necessary, our human team may perform an additional manual review to ensure no strong profile is missed.
The process is transparent, skills-based, and free of bias — focusing solely on your fit for the role.
Once the shortlist is completed, we share it directly with the company that owns the job opening. The final decision and next steps (such as interviews or additional assessments) are then made by their internal hiring team.
Thank you for your interest!
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