Senior CV ML Engineer

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Raw Ventures

WebsiteLinkedInAll Job Openings

11 - 50 employees

🧬 Biotechnology

📱 Media

🤖 Artificial Intelligence

Biotechnology • Media • Artificial Intelligence

<Raw Ventures> Raw Ventures is a venture studio and investment firm that backs and builds startups across MediaTech, HealthTech, biotech, and sustainability sectors using evergreen capital, hands-on advisory, and talent development. It operates an ecosystem combining investment (Evergreen), AI-powered advisory (Raw Advisory), and creative/talent support (Raw Creative) to help technologies move from proven concepts to practical impact, and it focuses on innovative content, healthcare and biotech ventures. The firm emphasizes building interconnected companies rather than isolated startups and publishes news about its portfolio and activity.

📋 Description

• Own the full model lifecycle — data, labeling, training, evaluation, deployment, monitoring, feedback • Improve detection/segmentation models across diverse real-world conditions, lighting, environments • Build labeling, testing, and validation processes with the validators team — taxonomies, guidelines, QA loops, active learning • Define evaluation methodologies; identify weak spots and fix them • Stay close to customers and product — what they pay for shapes model priorities • Productionize models on Triton — latency, throughput, cost • Drive research direction: pretraining, architectures, multi-stage pipelines

🎯 Requirements

• 5+ years CV/ML with senior depth • Deep understanding of the full CV model lifecycle • Track record of high-quality production CV models — robust across real conditions, edge cases handled • Methodological eye — you spot when evaluation, labeling, or training is broken and fix it • Product and business sense — you understand how models make money, don’t chase accuracy that doesn’t move the business • Hands-on YOLO (YOLO 11 ideal, any recent version counts) • Experience designing labeling/annotation processes with annotation teams • Roboflow workflows or comparable (dataset versioning, labeling, augmentation) • Triton deployment and optimization (or comparable serving infra) • MLOps fundamentals — experiment tracking, model versioning, evaluation, production monitoring • Strong PyTorch, production-grade Python (not just notebooks) • Russian — fluent or native (required) • English B1+

🏖️ Benefits

• Fully remote, CET hours • Real product impact at scale • Direct contact with leadership and engineering team • AI-augmented development culture • Competitive compensation, discussed individually