Job Title: Machine Learning Deployment Engineer

Redenlab is a global leader in speech analytics focused on advancing the development of new treatments and enabling earlier clinical insights in healthcare. We do this by optimising the measurement of brain health with our digital speech analytics platform. We are driven by the mission that through our work we impact the health of communities by delivering solutions that combine breakthrough clinical science with advanced technologies. We are inspired by the dedication of researchers and the resilience of patients, and we are strengthened by our 20-year heritage supporting them. We are always working to simplify the complex with solutions that offer insights and hope for the future of healthcare, particularly progressive brain diseases, and rare paediatric disorders.

Position Overview

Redenlab is looking for a versatile Machine Learning Deployment Engineer with a strong background in both model operationalization and fine-tuning/training to help scale our ML services. The ideal candidate will not only convert existing models into scalable APIs but also contribute to model improvement, validation, and deployment strategies. You will play a central role in end-to-end machine learning lifecycle, from proof-of-concept (PoC) development to cloud deployment, including GUI integration and scalable infrastructure setup.

Key Responsibilities

Model Training, Fine-Tuning & Validation

Collaborate with research and engineering teams to train and fine-tune ML models on domain-specific datasets.

Evaluate model performance across benchmarks and iterate based on results.

Build and validate proof-of-concept (PoC) models to support product direction and stakeholder needs.

API Development & Model Deployment

Convert standalone ML models into scalable, production-ready APIs.

Implement authentication and credit-based usage tracking.

Ensure robust access control and developer-friendly API documentation.

Performance Optimization & Scalability

Optimize inference pipelines for low-latency and high-throughput use cases.

Build scalable cloud architectures to support concurrent users and evolving workloads.

Apply best practices in resource management, autoscaling, and fault tolerance.

Cloud-Based GUI & Tooling

Develop intuitive, secure web-based interfaces for clients to interact with deployed models.

Ensure API and GUI integration provides a seamless user experience.

Maintain security compliance and responsive design standards.

Required Skills & Experience

Solid experience with model training and fine-tuning using TensorFlow, PyTorch, or Scikit-learn.

Proven ability to take ML PoCs to production, from experimentation to live deployment.

Proficient in API development using FastAPI, Flask, or Django.

Deep knowledge of cloud platforms (AWS, GCP, Azure) for scalable deployments.

Experience with Docker & Kubernetes for container orchestration.

Frontend development skills (React, Vue.js, or similar).

Working knowledge of database systems (SQL, NoSQL) for usage tracking and auth.

Experience with ML pipeline optimization for real-time and batch inference.

Qualifications

Experience integrating ML APIs into cloud platforms with CI/CD pipelines.

Familiarity with microservices architecture.

Experience designing or scaling ML systems in regulated or privacy-sensitive domains.

Why join us?

Redenlab is an agile biotechnology company based in Melbourne, Australia with team members in the USA, South America, and Europe. We are global leaders in speech analytics in clinical medicine, having pioneered this important type of behavioural testing for the pharmaceutical industry. Working together, we’ve become the world’s leading research-focused speech neuroscience group.

Redenlab embraces diversity and equal opportunity. We are committed to building a team that represents a variety of backgrounds, perspectives, and skills. Redenlab is an equal opportunity employer.

Location: Melbourne

Schedule: Full time

If you have, questions please check out www.redenlab.com