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Distinguished Engineer - Machine Learning (VP level) - (Remote - Europe)

Posted 5 days agoViewed

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💎 Seniority level: Vp, 10+ years

📍 Location: Spain, United Kingdom, Italy

🏢 Company: Jobgether👥 11-50💰 $1,493,585 Seed about 2 years agoInternet

⏳ Experience: 10+ years

🪄 Skills: LeadershipPythonArtificial IntelligenceMachine LearningPeople ManagementPyTorchCross-functional Team LeadershipAlgorithmsData scienceTensorflowCommunication SkillsStrategic thinkingSoftware Engineering

Requirements:
  • PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
  • 10+ years of experience in AI/ML research and development post-PhD, with proven success in leading large-scale projects and driving innovation beyond academia.
  • Expertise in AI/ML frameworks, deep learning algorithms, and hardware-optimized machine learning.
  • Proven leadership experience in managing senior engineers, influencing technical direction, and driving engineering excellence.
  • Strong communication skills with the ability to influence and engage executives, engineers, and external stakeholders.
  • A history of contributions to academic research, open-source projects, or industry consortiums is highly desirable.
Responsibilities:
  • Lead the development and execution of multi-year, company-wide AI and ML initiatives, ensuring scalable solutions that address both current and future business needs.
  • Provide strategic leadership by engaging with senior leadership, external partners, and industry groups, influencing the company’s direction and technical strategy.
  • Spearhead the research and development of next-generation AI and ML models, driving innovation and performance breakthroughs.
  • Foster a high-performance culture by mentoring and coaching senior engineers and contributing to recruitment efforts.
  • Represent the company at conferences and external forums, publishing research findings and contributing to industry discussions.
  • Collaborate closely with product and business teams to define roadmaps and drive alignment between technical capabilities and business goals.
  • Manage large-scale, high-impact projects, ensuring exceptional execution while navigating ambiguity and evolving requirements.
  • Drive continuous improvement through the adoption of industry best practices and cutting-edge research.
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