
Head of Applied Science - Clipchamp
- Brisbane, QLD
- Permanent
- Full-time
- Stay at the forefront of AI, generative media, and large language model (LLM) research, applying techniques such as prompt engineering, fine-tuning, and retrieval-augmented generation (RAG) to enhance Clipchamp’s video creation capabilities.
- Lead the design and development of advanced ML/NLP/CV models to power intelligent video editing, generation and personalisation.
- Architect and refine machine learning models (supervised and unsupervised) that optimise the relevance, quality and creativity of video outputs.
- Build and scale relevance and ranking systems tailored to video discovery and editing recommendations.
- Develop synthetic and real-world datasets for training and benchmarking AI models in video domains.
- Design rigorous evaluation methodologies that reflect real creator workflows and measure user-perceived quality.
- Continuously iterate using real user feedback, telemetry, and A/B testing to improve model precision, recall, and satisfaction.
- Partner closely with engineering and product teams to integrate AI models into Clipchamp’s editing, generation, and publishing workflows.
- Ensure models are production-ready, meeting standards for scalability, latency, security, compliance, and reliability in a cloud-based video platform.
- Translate creator needs into robust, AI-driven video features that operate seamlessly at Microsoft scale.
- Provide technical leadership across applied science initiatives, ensuring scientific rigour and innovative thinking.
- Mentor applied scientists and machine learning engineers, fostering best practices in research, coding, experimentation, and delivery.
- Recruit and nurture diverse talent, building a culture of creativity, collaboration, and high-impact innovation.
- Set a bold, creator-focused mission that unites the team around ambitious, measurable goals.
- Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 8+ years related experience (e.g., statistics, predictive analytics, research)
- OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research)
- OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ years related experience (e.g., statistics, predictive analytics, research)
- OR equivalent experience.
- 3+ years of people management experience.
- 4+ years of experience designing, running, and evaluating experiments, leveraging user feedback and telemetry to improve system performance.
- Deep expertise with large language models (LLMs), including techniques such as prompt engineering, fine-tuning, and retrieval-augmented generation (RAG).
- Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.
- Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering,
- OR related field AND 12+ years related experience (e.g., statistics, predictive analytics, research)
- OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering,
- OR related field AND 8+ years related experience (e.g., statistics, predictive analytics, research)
- OR equivalent experience.
- 7+ years of people management experience.
- 3+ years experience presenting at conferences or other events in the outside research/industry community as an invited speaker.
- Experience presenting as an invited speaker at conferences or other industry/research community events.
- 7+ years of research experience in academic or industry environments.
- 5+ years of experience developing and deploying live production systems within a product team.
- 7+ years of experience delivering products or systems across multiple phases of the product lifecycle, from concept through to launch.
- Solid understanding of modern machine learning techniques, including natural language processing, deep learning, and their application to real-world scenarios.
- Demonstrated success in applying LLMs and advanced NLP algorithms to production-scale problems.
- 8+ years of hands-on experience building and deploying machine learning or AI solutions in production environments, with a proven track record of taking projects from prototype to large-scale release.
- Solid programming skills in languages such as Python (and/or C++/Java) and proficiency with ML frameworks/tools such as PyTorch or TensorFlow.
- Advanced analytical skills for working with large-scale datasets and assessing model performance, including defining and tracking ML metrics (e.g., precision, recall), applying user feedback to improve models, and iteratively diagnosing model behaviour.