Computer Vision/Machine Learning Engineer

Job Summary

The Select Group is looking to add a Computer Vision and Multimodal AI Engineer to a highly innovative AI team to help shape the next generation of intelligent, AI-powered business solutions.

What You'll Be Helping Build

• Intelligent systems that analyze and understand visual data at scale.
• Multimodal AI solutions that combine images, language, and reasoning to deliver richer insights.
• Agenetic AI workflows capable of surfacing recommendations and automating decision-making processes.
• Production-grade AI applications that support both operational efficiencies and customer-facing experiences.
• Scalable architectures that enable rapid experimentation while supporting long-term growth.

What Success Looks Like

The right person will be comfortable owning the full lifecycle of machine learning initiatives—from designing experiments and validating assumptions to deploying models and continuously improving performance.

Technical Environment

• Computer Vision and Machine Learning
• Vision-Language Models (CLIP, BLIP, Gemini, and similar frameworks)
• Multimodal AI and reasoning systems
• Agentic AI workflows
• Python
• PyTorch, TensorFlow, CoreML, or similar ML frameworks
• Cloud-based AI deployment environments
• Model evaluation, optimization, and performance tuning

Who Tends to Excel in This Environment

• Engineers who have successfully deployed machine learning solutions into production.
• Professionals who enjoy building and testing new ideas rather than simply maintaining existing systems.
• Individuals who can move comfortably between research, experimentation, engineering, and business conversations.
• Practitioners who are excited about emerging technologies in multimodal AI, visual reasoning, and autonomous agents.
• Self-starters who can operate independently while collaborating effectively across engineering, product, and business teams.

Why This Opportunity Stands Out

• Work on some of the most rapidly evolving areas of artificial intelligence.
• Opportunity to influence architecture, strategy, and technical direction.
• Exposure to Computer Vision, multimodal AI, VLMs, and agentic systems in production environments.
• Collaborative team culture that values experimentation, innovation, and measurable business impact.
• Long-term engagement supporting the development of next-generation AI capabilities.