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