Lead Machine Learning Engineer

vor 1 Woche

Graz, Steiermark, Österreich Blackshark Vollzeit
About the Role

We are seeking an exceptional Technical Director to lead our Machine Learning team at Blackshark, a pioneering company at the forefront of geospatial AI development.

Key Responsibilities
  • Strategic Leadership: Collaborate closely with product management on roadmap planning and milestone estimation, driving innovation in a fast-paced, high-impact environment.
  • Team Management: Mentor team members, conduct regular check-ins, and foster professional development, ensuring the growth and success of the Machine Learning team.
  • Technical Vision: Stay at the cutting edge of ML vision research, providing insights to the team and stakeholders, and creating and driving the technical vision for the ML team, aligning with product and market strategies.
  • System Design: Lead ML system design and architecture decisions, ensuring the development of production-ready systems.
  • Code Reviews: Perform code reviews and provide constructive feedback to team members, promoting high-quality code and best practices.
  • Customer Support: Serve as the primary technical contact for ML product customers, providing expert guidance and support.
  • Reporting: Prepare and review technical reports for internal and external consumption, ensuring clear and concise communication of technical concepts.
Qualifications
  • Academic Background: Ph.D. or equivalent experience in Machine Learning, Computer Vision, or a related field.
  • Research Experience: Proven track record in academia, with published research in top-tier ML/CV conferences or journals.
  • Engineering Experience: Extensive engineering experience, demonstrating the ability to translate research into production-ready systems.
  • Leadership Skills: Strong leadership skills, with experience managing and mentoring technical teams, attracting and nurturing top technical talent.
  • Technical Expertise: Deep understanding of state-of-the-art ML and computer vision techniques.
  • Communication Skills: Excellent communication skills, able to convey complex technical concepts to both technical and non-technical audiences.
  • Language Skills: Fluent in English (both written and spoken).
Preferred Qualifications
  • Geospatial Experience: Experience with geospatial data and technologies.
  • Cloud Computing: Familiarity with cloud computing platforms (AWS, Azure).
  • MLOps: Knowledge of MLOps and ML systems at scale.
  • Programming Languages: Languages: Python.
  • Computer Vision: Computer Vision: OpenCV, PIL.
  • Version Control: Version Control: Git, GitLab.

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