About The Position

We are seeking an experienced Engineering Manager to lead a high-performing Machine Learning and Computer Vision team focused on advancing 3D AI technologies. In this role, you will define technical strategy, drive execution of machine learning initiatives, and foster a culture of innovation and excellence. You will collaborate across product, engineering, and research teams to implement scalable ML solutions, manage complex datasets, and ensure robust deployment of models. This role combines people management, technical leadership, and hands-on problem solving in a fast-paced, growth-oriented environment. Ideal candidates are passionate about 3D deep learning, generative AI, and leading teams to deliver impactful, high-quality ML products.

Requirements

  • Bachelor’s degree in Computer Science, Electrical Engineering, Robotics, or related field with strong focus on ML/Computer Vision.
  • Extensive experience with 2D and/or 3D deep learning frameworks, preferably PyTorch.
  • 6+ years of industry experience in applied machine learning (or 5+ years with a PhD), including at least 1 year in a leadership role.
  • Proven people management skills with experience developing and mentoring high-performing teams.
  • Demonstrated ability to lead cross-functional projects involving product, engineering, and research teams.
  • Strong coding skills in Python and familiarity with ML frameworks and 3D ML data types (point clouds, meshes, volumetric data).
  • Experience in scalable model deployment and MLOps best practices.
  • Excellent analytical, problem-solving, and communication skills.

Responsibilities

  • Lead and manage a team of ML engineers, scientists, and researchers, fostering mentorship, development, and retention.
  • Execute the machine learning roadmap, focusing on 3D deep learning, computer vision, and generative AI applications.
  • Partner with product, engineering, and research stakeholders to align technical strategy with business objectives.
  • Develop, implement, and evaluate computer vision models to extract insights from unstructured 3D data.
  • Research state-of-the-art methods for ML model development and identify opportunities to enhance existing product lines.
  • Manage large-scale datasets and implement evaluation methods to ensure model accuracy and reliability.
  • Establish best practices for MLOps pipelines to ensure scalable, robust, and maintainable deployment of ML models.

Benefits

  • Competitive salary and equity compensation.
  • Comprehensive, regionally tailored healthcare, dental, and mental health support.
  • Generous paid time off and parental planning resources.
  • Retirement savings plans and financial wellness support.
  • Flexible remote work environment with global collaboration opportunities.
  • Inclusive and supportive culture with opportunities for professional growth and mentorship.
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