Computer Vision Engineer

We are seeking a dedicated, research-driven professional with a strong foundation in mathematics and algorithmic problem-solving. The ideal candidate will have 3+ years of full-time industry experience (non-freelance) in computer vision and MLOps, with a proven track record of delivering rapid, quality solutions in a collaborative team environment. A Master’s degree is preferred over a Bachelor’s, and candidates should not be concurrently pursuing academic coursework or scholarships in AI/ML.

 Computer Vision & MLOps Development: Design, develop, and deploy robust computer vision solutions and scalable MLOps pipelines for production environments.

 Research & Innovation: Lead and contribute to advanced research projects, leveraging strong mathematical and algorithmic expertise to implement state-of-the-art machine learning solutions.

 Project Delivery: Ensure quick and efficient delivery of projects and products, focusing on continuous improvement and innovative problem-solving.

 Team Collaboration: Work collaboratively with cross-functional teams on multiple projects, fostering an environment of clear communication and proactive issue resolution.

 Problem Identification & Resolution: Quickly identify potential issues or failures, communicate these transparently, and proactively drive solutions without creating dependencies on others.

 Code Excellence: Write clean, maintainable code primarily in Python; experience in C++ is a plus. Good with Nvidia Triton Server, Deepstream and other ML optimization and serving frameworks.

Required Qualifications:

 Experience: Minimum of 3 years of full-time, non-freelance industry experience in computer vision and MLOps.

 Education: Master’s degree (MS) in a relevant field is preferred over a Bachelor’s degree. Candidates actively pursuing AI/ML coursework or scholarships for further academic programs (MS/PhD) will not be considered.

Technical Skills:  

• Proficiency in Python; C++ is a plus.  
• Strong grasp of mathematics and algorithmic concepts.  
• Proven experience in deploying ML models in production environments.

 Soft Skills:

• Excellent communication skills and a proactive approach to problem-solving.  
• Ability to work well in a team and collaborate on multiple projects simultaneously.  
• Commitment to a minimum tenure of one year with a focus on long-term growth and impact.

Preferred Qualifications:

•  Familiarity with Large Language Models (LLMs) is a bonus.
• Demonstrated track record of research and innovative project contributions.
• Experience with deploying scalable MLOps pipelines and managing end-to-end machine learning workflows.

Additional Considerations:

 Commitment:   The role requires a minimum commitment of one year; we are seeking candidates who are not looking to switch roles frequently.

Autonomy:  The successful candidate will be self-reliant, capable of independently managing challenges, and will proactively flag any issues early (“fail quick”) to keep projects on track.