Lead Machine Learning Researcher

Position Title: Machine Learning Engineering Lead
Location: Melbourne Australia
Job Type: Full-Time

Role Overview:

As the Machine Learning Engineering Lead, you will be responsible for leading the development, deployment, and scaling of machine learning and AI-driven solutions across our organization.

This role requires a deep understanding of generative AI (GenAI), autonomous agents, deep learning, machine learning, and statistics, combined with hands-on experience in coding and productionizing ML-enabled applications.

You will work closely with cross-functional teams, including data scientists, software engineers, product managers, and stakeholders, to deliver innovative and impactful AI solutions that drive business value.

Key Responsibilities:


* Leadership & Strategy:
+ Lead the design, development, and deployment of machine learning models, with a focus on generative AI and autonomous agent capabilities.
+ Mentor and guide a team of machine learning engineers, fostering a culture of innovation, collaboration, and continuous improvement.
+ Stay up-to-date with the latest advancements in AI/ML technologies and apply them to solve complex business challenges.


* Technical Development:
+ Architect, design, and implement scalable ML systems and pipelines for real-time and batch processing, ensuring high availability, performance, and reliability.
+ Develop and productionize machine learning models, including deep learning, statistical models, and advanced algorithms, using best practices in software engineering.
+ Utilize generative AI techniques and autonomous agent frameworks to create intelligent systems capable of autonomous decision-making and task execution.
+ Ensure the integration of ML models into production environments, optimizing for scalability, robustness, and security.
 


* Collaboration & Communication:
+ Collaborate with data scientists to transform research prototypes into production-ready models, ensuring code quality and maintainability.
+ Work closely with product managers and stakeholders to define AI/ML use cases, requirements, and deliverables.
+ Communicate complex technical concepts to non-technical stakeholders, providing insights and recommendations based on data-driven analysis.


* Innovation & Continuous Improvement:
+ Lead the evaluation and implementation of new tools, frameworks, and technologies that enhance the efficiency and effectiveness of ML workflows.
+ Identify opportunities to leverage AI/ML to automate processes, improve decision-making, and enhance user experiences.
+ Promote a culture of experimentation, encouraging the team to explore new ideas and approaches to solving business problems.

Required Skills & Qualifications:


* Educational Background:
+ Bachelor's or Master’s degree in Computer Science, Machine Learning, Dat...