At a Glance
- Tasks: Research and develop cutting-edge AI solutions for speech and language technologies.
- Company: Join Redenlab, a pioneering biotech company transforming brain health measurement.
- Benefits: 12-month contract with opportunities for impactful research and collaboration.
- Other info: Collaborate with industry leaders and contribute to meaningful health outcomes.
- Why this job: Make a real difference in healthcare by advancing innovative AI technologies.
- Qualifications: Master's or PhD in relevant fields with strong machine learning experience.
The predicted salary is between 63000 - 77000 $ per year.
This 12-month contract role offers a unique opportunity to work at the forefront of machine learning research, clinical innovation, and speech and language technologies. You will play a key role in developing next-generation AI solutions that advance speech, language, and digital health applications, contributing to innovative technologies that have the potential to drive meaningful improvements in patient care and health outcomes.
Key responsibilities
- Research, develop, train and evaluate machine learning and deep learning models for speech, audio and language analysis, including AI-derived digital biomarkers.
- Adapt and fine-tune state-of-the-art models such as wav2vec 2.0, HuBERT, WavLM, Whisper, transformers, LLMs and multimodal architectures for specialised datasets.
- Design rigorous experiments incorporating appropriate baselines, cross-validation, external validation and statistical model comparison.
- Conduct systematic benchmarking of new AI technologies against established methods and research standards.
- Monitor emerging developments in machine learning and assess their relevance to current and future research programs.
- Evaluate model robustness and generalisability across speakers, languages, recording environments and clinical populations.
- Perform error analysis and identify potential issues related to bias, fairness, overfitting and data leakage.
- Contribute to peer-reviewed publications, conference presentations and research grant applications.
- Collaborate with academic, clinical and industry partners to advance research outcomes.
- Maintain clear documentation of methodologies, experiments, model performance and research findings.
About you
- Master's degree or PhD (or near completion) in Machine Learning, Artificial Intelligence, Computer Science, Speech/Signal Processing, Natural Language Processing, Computational Linguistics, Biomedical Engineering or a related discipline.
- Strong experience developing, training and evaluating machine learning and deep learning models.
- Advanced Python programming skills.
- Hands-on experience with PyTorch and modern AI/ML frameworks.
- Experience working with Hugging Face, pretrained models and foundation models.
- Strong understanding of experimental design, validation methodologies and reproducible research practices.
- Knowledge of model evaluation, overfitting, data leakage, generalisability and statistical comparison techniques.
- Experience working with complex real-world datasets.
- Familiarity with Git and Linux/GPU-based research environments.
- Excellent analytical, problem-solving and scientific communication skills.
About us
Redenlab is an agile biotechnology company dedicated to advancing the development of new treatments and enabling earlier clinical insights in healthcare. We achieve this by transforming the measurement of brain health through our innovative digital speech analytics platform. Our mission is to improve health outcomes by combining breakthrough clinical science with advanced technologies, delivering solutions that make a meaningful difference to patients, researchers and healthcare. Strengthened by more than 20 years of experience supporting clinical research, we are committed to simplifying complexity and unlocking new possibilities in healthcare.
Machine Learning Research Scientist in Melbourne employer: Redenlab
Redenlab offers a dynamic work environment where employees can engage in cutting-edge research and development in the fields of clinical operations and machine learning. The company emphasizes building high-performing teams and improving operational processes, providing opportunities for professional growth and collaboration across various disciplines. Employees benefit from a hands-on leadership approach that fosters innovation and exceptional customer outcomes.
