Machine Learning Engineering Manager
icare NSW · Sydney, New South Wales, Australia
- On site
- Full-time
- A$150,000 / year
- Sydney, New South Wales, Australia
Job highlights
- Lead ML engineering and MLOps practices.
- Deploy AI and ML models into production.
- Mentor and develop a talented team.
- Collaborate across diverse functional teams.
- Drive innovation in AI solutions.
About the role
About the Role
The Machine Learning Engineering Manager is the foundational engineering lead within icare’s Data Science and AI function. The role begins as a hands-on technical lead responsible for establishing robust ML engineering, MLOps and LLMOps practices that enable secure, reproducible, and reliable deployment of AI systems.
Benefits
- A corporate wellbeing program with subsidised gym membership, free flu vaccinations and health check programs
- 17.5% annual leave loading
- icare day - access to an extra day’s leave
- Comprehensive learning and development support aligned to icare’s Core Capabilities.
- Our People Awards - On-the-spot Recognition, Quarterly Values Awards & Our People Annual Awards
- Access to our Employee Assistance Program
Duties
It’s an exciting time at icare where no two days are the same. In this role you will:
- Deliver data and Machine Learning and AI models that align to the overall technical, data and AI strategy, making trade-offs where appropriate.
- Deliver coherent and technically feasible ML, LLM and AI system designs with multiple components interacting across API or system boundaries.
- Design ML, LLM and AI system metrics and an implementation and monitoring plan to ensure ML, LLM and AI systems are performant through the lifetime of the system.
- Identify and resolve technology limitations, designing sustainable long-term solutions that minimise risk and maximise value.
- Drive innovation by formulating complex business objectives into intelligent and scalable ML, LLM or AI solutions.
- Drive the creation and maintenance of standards to ensure quality delivery of the ML, LLM and AI solutions across the organisation.
- Formulate plans to improve ML Engineer and Data Scientist efficiency as measured by cycle time, or other similar measurements.
- Provide constructive feedback and hands-on technical guidance to members of the Data Science and Machine Learning engineering teams through the lifecycle of an ML, LLM or AI project.
- Partner with the Head of Data Science and AI and the Data Science Manager to set the cultural tone for the team, supporting an environment of psychological safety, empathy and productivity.
- Help the ML Engineering team build relationships across icare, creating connection across teams.
- Structure the ML Engineering team so the right people are in the right roles with clearly defined responsibilities.
- Foster the career growth of ML Engineers and Data Scientists through coaching, mentoring and on-the-job-experiences.
- Interview and assess candidates to help us build a diverse and talented ML Engineering team.
- Partner with Data Platforms and Insights, Architecture, Security, Privacy, and Governance to ensure ML, MLOps, LLMOps and practices align with enterprise standards.
- Build deep cross-functional relationships, facilitate the right conversations, balancing multiple perspectives, and engage in productive conflict with thoughtful questioning/challenging, disagreeing and committing when necessary to move decisions forward.
- Advise on the technical ML, MLOps. LLMOps components of an enterprise level AI strategy.
- Resolve cross-team dependencies to ensure the successful execution of ML, LLM, and AI projects.
Skills & Experience
- Minimum 8 years’ experience in Machine Learning Engineering, Machine Learning Operations, or DevOps roles.
- Experience leading or mentoring teams.
- Experience deploying ML systems into production environments (cloud or hybrid).
- Experience collaborating with Data Scientists, Architects, Security, Privacy, Governance and Platform teams.
- Experience with AWS and/or Snowflake based ecosystems.
- Experience working in an Agile Scrum environments and in the use of work tracking tools such JIRA.
Culture
We know our strength comes from the diversity of our people and would encourage people with different experiences and backgrounds to apply. We are committed to our people’s development so the people of NSW can thrive.
About the Company
We care for the people of NSW, building confidence and trust so our communities can thrive. We make the complex simple, so our schemes deliver better outcomes for people and communities. Whether a person is severely injured in the workplace or on our roads, icare supports their long-term care needs to improve quality of life, including helping people return to work. For more information about icare visit our website. icare operates a direct sourcing model so no agency introductions will be accepted. We are a Circle Back Initiative Employer - we commit to respond to every applicant. A talent pool may be created through this recruitment process. Please note that you must be an Australian citizen, permanent resident of Australia, New Zealand citizen with a current New Zealand passport or have unrestricted working rights to apply for this role.
Key skills/competency
- Machine Learning Engineering
- MLOps
- LLMOps
- AI Strategy
- Team Leadership
- Agile Scrum
- AWS
- Snowflake
- DevOps
- System Design
Skills & topics
- Machine Learning
- ML Engineering
- MLOps
- LLMOps
- AI
- Manager
- Leadership
- DevOps
- AWS
- Snowflake
- Agile
- Sydney
How to get hired
- Tailor your resume: Highlight your Machine Learning Engineering, MLOps, and leadership experience, using keywords from the job description.
- Showcase deployment experience: Detail your successful ML system deployments in production, specifying cloud or hybrid environments.
- Emphasize collaboration: Provide examples of working effectively with Data Scientists, Architects, Security, and Platform teams.
- Prepare for technical and behavioral questions: Be ready to discuss your approach to ML system design, monitoring, and team leadership in an Agile setting.
- Demonstrate AWS/Snowflake proficiency: Be prepared to discuss your experience with these ecosystems in relation to ML model deployment and management.
Technical preparation
Deepen understanding of ML system architecture.,Practice MLOps and LLMOps best practices.,Review AWS and Snowflake ML capabilities.,Prepare to discuss production deployment strategies.
Behavioral questions
Describe leading and mentoring a team.,How do you resolve cross-team dependencies?,Share an experience driving innovation.,How do you foster team psychological safety?
Frequently asked questions
- What are the primary responsibilities of a Machine Learning Engineering Manager at icare NSW?
- As a Machine Learning Engineering Manager at icare NSW, you will be the lead engineer for the Data Science and AI function. Your responsibilities include establishing ML engineering, MLOps, and LLMOps practices, designing and deploying AI/ML models, resolving technical limitations, driving innovation, and fostering the career growth of the ML Engineering and Data Science teams.
- What experience is required for the Machine Learning Engineering Manager role at icare NSW?
- The role requires a minimum of 8 years' experience in Machine Learning Engineering, Machine Learning Operations, or DevOps. You'll also need experience leading or mentoring teams, deploying ML systems into production, collaborating with various technical teams, and familiarity with AWS and/or Snowflake ecosystems, as well as Agile Scrum environments.
- What kind of work environment can I expect as a Machine Learning Engineering Manager at icare NSW?
- You can expect a hybrid work environment at the Kent Street, Sydney office. icare fosters a culture that values diversity, people's development, and aims for psychological safety, empathy, and productivity within its teams.
- What are the benefits of working as a Machine Learning Engineering Manager at icare NSW?
- icare NSW offers a comprehensive benefits package including a corporate wellbeing program, subsidised gym membership, annual leave loading, an extra day's leave (icare day), learning and development support, recognition awards, and an Employee Assistance Program.
- How does icare NSW support the career growth of its Machine Learning Engineers and Data Scientists?
- The Machine Learning Engineering Manager plays a key role in fostering career growth through coaching, mentoring, and on-the-job experiences. icare is committed to people's development, providing learning and development support aligned to its Core Capabilities.
- What technologies and tools are important for the Machine Learning Engineering Manager at icare NSW?
- Key technologies and tools include AWS and/or Snowflake ecosystems for ML deployments. Experience with MLOps, LLMOps, and Agile Scrum using tools like JIRA is also essential for this role.
- What is icare NSW's approach to recruitment for the Machine Learning Engineering Manager position?
- icare NSW operates a direct sourcing model and is a Circle Back Initiative Employer, committing to respond to every applicant. They may also create a talent pool from this recruitment process.