Job description

About the Role Our client is an innovative AI-driven retail security firm currently experiencing 10x growth. As they scale from individual retailers to massive enterprise clients with 100+ locations, they are seeking a Founding Applied Scientist to build their core AI capabilities from the ground up. This is not a "pure research" role. You will be a hands-on builder owning the full model development lifecycle. You’ll be responsible for everything from data collection strategy and quality assessment to training, inference optimization, and shipping production-quality code. Reporting directly to the CTO, you will collaborate with a distributed engineering team to deliver computer vision solutions that have an immediate impact on retail safety and operations. Key Responsibilities • Lead Model Development: Take full ownership of the model lifecycle, including production training, optimization, and inference deployment. • Bridge Research & Engineering: Write substantial, production-ready code (Python) to ensure CV models are successfully deployed via cross-functional engineering teams. • Strategic Data Planning: Design and implement data collection and quality assessment frameworks to improve model accuracy in real-world retail environments. • Technical Communication: Present complex technical findings and AI roadmaps to both engineering teams and executive leadership. What We’re Looking For • Experience: 3+ years of professional experience in Applied Science, ML Engineering, or Computer Vision roles. • Proven Track Record: You have shipped customer-facing products and have deep experience with real-world CV applications (e.g., YOLO or similar architectures), rather than just academic projects. • Technical Mastery: Advanced proficiency in Python with PyTorch or TensorFlow . • Academic Background: Master’s degree or PhD in Computer Science, Machine Learning, or Computer Vision. • Collaborative Spirit: Comfortable working in a fast-paced startup environment and collaborating with distributed teams across time zones (specifically Turkey-based engineering).

Requirements

Must-haves

Lead Model Development: Take full ownership of the model lifecycle, including production training, optimization, and inference deployment.
Bridge Research & Engineering: Write substantial, production-ready code (Python) to ensure CV models are successfully deployed via cross-functional engineering teams.
Strategic Data Planning: Design and implement data collection and quality assessment frameworks to improve model accuracy in real-world retail environments.
Technical Communication: Present complex technical findings and AI roadmaps to both engineering teams and executive leadership.
What We’re Looking For
Experience: 3+ years of professional experience in Applied Science, ML Engineering, or Computer Vision roles.
Proven Track Record: You have shipped customer-facing products and have deep experience with real-world CV applications (e.g., YOLO or similar architectures), rather than just academic projects.
Technical Mastery: Advanced proficiency in Python with PyTorch or TensorFlow .
Academic Background: Master’s degree or PhD in Computer Science, Machine Learning, or Computer Vision.
Collaborative Spirit: Comfortable working in a fast-paced startup environment and collaborating with distributed teams across time zones (specifically Turkey-based engineering).

Nice-to-haves

None flagged.

Application prep

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Keywords to mirror

aipythonmlmachine learning

Platform: manatal
Effort: medium

Benefits

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