Machine Learning Ops Engineer
Singtel is hiring a Machine Learning Ops Engineer in Sydney, Australia. Level rates it ; you can apply on Singtel.
Level's read on this job
- Builds AI ●●●● is how Level rates this role: the job is building AI systems.
- The posting mentions MLflow, Databricks and MLOps among its tools and skills.
- Singtel has 475 other open roles on Level.
- Posted in the last few days.
AI in this role
Optus is an Australian telecommunications company, delivering more than 11 million services to our customers every day across mobile, broadband and digital solutions.
Based in Macquarie Park, Sydney, join a newly established team focused on protecting Australians from increasingly sophisticated scam activity. As a Machine Learning Ops Engineer, you'll play a critical role in building, deploying and scaling machine learning solutions that power Optus' scam detection capabilities.
We are open to applicants from Melbourne.
Working across engineering, data and cyber security teams, you'll help bring machine learning models into production, improve detection outcomes and contribute to solutions that have a direct impact on customer protection at scale.
What You’ll Do
- Build, deploy and maintain machine learning pipelines that support model training, testing and production deployment.
- Develop and optimise feature engineering workflows and feature stores to improve model performance and scalability.
- Automate model deployment, monitoring and retraining processes using MLOps and CI/CD best practices.
- Partner with Data Engineers, Software Engineers and business stakeholders to deliver reliable machine learning solutions.
- Monitor production model performance and proactively identify opportunities to improve accuracy, efficiency and reliability.
- Support model governance activities including documentation, auditability and lifecycle management.
- Troubleshoot production issues and implement enhancements to ensure models remain effective as scam patterns evolve.
- Contribute to the ongoing development of machine learning standards, frameworks and best practices across the team.
What You Bring
- Extensive experience in Machine Learning Engineering, MLOps, Data Engineering or a similar discipline.
- Strong Python development skills and experience deploying machine learning solutions into production environments.
- Experience building and maintaining automated training, deployment and monitoring pipelines.
- Knowledge of machine learning lifecycle management, version control and CI/CD frameworks.
- Experience working with large data sets and distributed data processing environments.
- Familiarity with modern machine learning platforms such as Databricks, MLflow, Spark or similar technologies.
- Strong problem-solving skills with the ability to identify, analyse and resolve complex technical challenges.
- Excellent stakeholder engagement and communication skills, with the ability to translate technical concepts for diverse audiences.
The good stuff….
- Competitive remuneration and employee discounts. Make life easier (and more affordable) with $80 monthly credit and 25% off Optus products and unique shopping discounts with our retail partners.
- Flexible working arrangements with opportunities to work three days in the office, two days remote or home.
- Vibrant and collaborative office campus that includes cafes, convenience store, chill out zones, GP, post office, gym and on-site childcare centre.
- Competitive leave policies, including additional 'Connected’ days to focus on culture, family, health, community, or whatever’s important to you.
- We support growing families with inclusive, carer-neutral paid Parental Leave of up to 16 weeks.
- Build meaningful connections through employee-led networks and diversity initiatives including Culture Connect, Elevate Women, Disability Network and Express Yourself (LGBTQIA+).
- Put your wellbeing first with free access to counselling and support services, 24/7 — in-person, by phone, SMS, or video.
- Free Optus bus from Macquarie University Metro Station (every 6-8 minutes); morning and afternoon.
At Optus, we are strengthened by others and that means valuing diversity and saying ‘yes’ to embracing individual differences. We are committed to ensuring that our application process provides an equal employment opportunity to all job seekers, including individuals from diverse gender, cultural and linguistic backgrounds, individuals with a disability, individuals identifying as being part of the LGBTQIA+ community, individuals who may have served in the armed forces or who identify as Aboriginal and/or Torres Strait Islander. We also want to do our best to make our recruitment process inclusive. If you require any adjustments or accessibility support to participate fairly and equitably in the recruitment process, please email AccessibleRecruitment@optus.com.au or call 1800 309 170.
For more information on Diversity, Inclusion & Belonging at Optus, please visit https://www.optus.com.au/about/inclusion-diversity.
#LI-CS1
How we rate this
Machine Learning Ops Engineer at Singtel rates 87 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- How do you monitor a model once it's live, and how do you know it needs retraining?
- Walk me through how you've used MLflow in your day-to-day work.
- What are the limits of Databricks that you've run into, and how did you work around them?
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: ML Ops, MLflow, and Databricks. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
Get your CV reviewed before you apply
Send your CV and the role you want next. Your review arrives by email within 3 days.
Get new data jobs (Builds AI ●●●●) by email
One email a week, each job rated for how much AI is in the work. No recruiter spam, unsubscribe in one click.
Free.
Similar roles
Data roles that build AI, at other companies.
What kind of AI work fits you?
Answer 12 practical questions in about three minutes. Get a simple profile, the work it points to, and live roles to explore next.
Find my next step