Senior Artificial Intelligence Engineer at Golftrak Pty Ltd
Melbourne, Victoria, Australia -
Full Time


Start Date

Immediate

Expiry Date

17 May, 25

Salary

150000.0

Posted On

17 Feb, 25

Experience

3 year(s) or above

Remote Job

No

Telecommute

No

Sponsor Visa

No

Skills

Machine Learning, Scikit Learn, Mobile Apps, Performance Metrics, Engineers, Opencv, Golf, Python, Teams, Sports, Keras, Numpy, Technology, Software, Communication Skills, Computer Science, Pandas, Computer Vision, Software Development, Data Integration

Industry

Information Technology/IT

Description

ABOUT US:

At GolfTrak, we’re revolutionizing the way golfers improve their game. Our cutting-edge golf simulation software brings high-performance data analysis to your fingertips, enabling players to track, analyze, and improve their performance on the go. We are passionate about blending sports, technology, and innovation to create a truly game-changing experience. Join us on our mission to empower players of all levels with real-time insights and performance tracking.

JOB DESCRIPTION:

We are looking for a talented Senior Artificial Intelligence Engineer with a strong background in Computer Vision to help us take our sports performance technology to the next level. In this role, you will leverage your expertise to develop intelligent models, improve real-time data capture, and enhance the user experience of our mobile launch monitor app. If you are excited by the idea of using data and machine learning to shape the future of sports performance, we want to hear from you!

MUST-HAVE QUALIFICATIONS:

  • A formal degree in Computer Science from a reputed university.
  • Proven track record in implementing Computer Vision pipelines.
  • 3+ years of experience as an Artificial Intelligence Engineer/Data Scientist, with a focus on Computer Vision and Machine Learning.
  • Strong experience with computer vision frameworks such as OpenCV.
  • Strong experience with machine learning frameworks such as TensorFlow, Keras, PyTorch, or similar.
  • Proficiency in Python and experience with data science libraries like NumPy, Pandas, and Scikit-learn.
  • Familiarity with mobile development environments (iOS, Android) and experience integrating machine learning models into mobile apps.
  • Professional experience in working with golf launch monitor technology.
  • Knowledge of performance metrics used in sports, particularly in golf.
  • Experience in agile software development or similar methodologies.
  • Experience leading a team of Engineers.
  • Strong communication skills, with the ability to explain complex technical concepts to diverse teams and stakeholders.

PREFERRED QUALIFICATIONS:

  • Experience with cloud computing platforms (AWS, GCP, etc.) for scaling machine learning models.
  • Familiarity with sensor data integration and hardware-to-software communication for real-time performance tracking.
  • An understanding of user experience (UX) design and its impact on mobile app performance.
Responsibilities
  • Develop ML and CV algorithms and train deep neural networks.
  • Design algorithms that process, interpret, and present key metrics in golf (e.g., ball speed, launch angle, spin rate, etc.) to users in real time.
  • Lead and manage a team of Junior AI Engineers and Data Engineers for product development.
  • Work closely with mobile app developers to integrate machine learning models and improve the app’s overall functionality and user experience.
  • Design and implement pipelines for generating and processing synthetic datasets.
  • Design and implement cloud-based inference pipelines for real-time processing.
  • Analyze user data to uncover patterns and trends that can lead to actionable insights for players.
  • Collaborate with cross-functional teams to enhance the app’s features, ensuring it meets the needs of both casual players and professionals.
  • Stay up-to-date with advancements in computer vision, deep learning, and mobile technologies to bring the best possible solutions to market.
  • Implement Proof of Concepts (POCs) from state-of-the-art (SOTA) computer vision research papers.
  • Create and maintain efficient data pipelines to process large volumes of sports performance data.
  • Communicate technical insights to both technical and non-technical stakeholders, ensuring alignment across teams.
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