Machine Learning Engineer, Automated Calibration Services

Sqc Silicon Quatum Computing; Sydney; Hybrid; AUD 150,000 - 200,000; Full time

Benefits offered by this job

Bonus scheme

Hybrid work in Sydney

Autonomy to lead initiatives

Collaborative team culture

Job summary

Atlassian in Sydney is seeking a Senior Machine Learning Engineer to design, build and operate ML pipelines in production. You will own end-to-end aspects from data processing to deployment, collaborating with data scientists and software engineers in a hybrid work setup.

The role emphasizes building robust Python services, scalable APIs, and CI/CD for ML systems, with a focus on production quality and business value. 4+ years of ML experience is expected, including LLM-based workloads.

Qualifications

• Proven production ML experience including deploying models to production
• Strong Python skills with ML/data libraries
• Understanding of end-to-end ML lifecycle
• Experience building APIs, CI/CD pipelines, automation

Responsibilities

• Develop and refine predictive and forecasting models
• Build and scale optimisation frameworks
• Design and maintain scalable backend services, APIs and data layers in Python
• Architect event-driven cloud infrastructure using IaC and orchestration
• Take POCs through to production with clean, tested code and CI/CD practices

Skills

Python

LLM systems

Kotlin

APIs

CI/CD

Docker

Kubernetes

Terraform

Data pipelines

Education

Bachelor's or Master's in CS/SE/Data Eng/Applied AI

Tools

Terraform

Docker

Kubernetes

Job description

Senior Machine Learning Engineer / Permanent / Sydney / up to $200,000 + super + bonus

About the Company

Our client is a growing data and analytics driven SaaS platform with an established customer base and a proven product. They're focused on building a sustainable, long‑term business and offer hybrid working in Sydney.

About the Role

This is a software engineering role applied to machine learning. You'll design, build and automate the infrastructure and tooling behind data science and product workflows, delivering reliable ML pipelines into production. You'll work closely with experienced data scientists and engineers, with genuine ownership of solutions from design through to delivery.

Benefits

• Salary range of $150,000 to $200,000+ super (depending on experience)
• Autonomy to lead initiatives and help shape ML engineering practices
• A collaborative team with a strong feedback culture

Senior Machine Learning Engineer / Permanent / Sydney / up to $200,000 + super + bonus

About the Company

Our client is a growing data and analytics driven SaaS platform with an established customer base and a proven product. They're focused on building a sustainable, long‑term business and offer hybrid working in Sydney.

About the Role

This is a software engineering role applied to machine learning. You'll design, build and automate the infrastructure and tooling behind data science and product workflows, delivering reliable ML pipelines into production. You'll work closely with experienced data scientists and engineers, with genuine ownership of solutions from design through to delivery.

Benefits

• Salary range of $150,000 to $200,000+ super (depending on experience)
• Bonus scheme
• Autonomy to lead initiatives and help shape ML engineering practices
• A collaborative team with a strong feedback culture

Duties / Key Responsibilities

• Develop and refine predictive and forecasting models that feed directly into customer decision‑making
• Build and scale optimisation frameworks to solve complex, constraint‑based problems
• Design and maintain scalable backend services, APIs and data layers in Python
• Architect event‑driven cloud infrastructure using infrastructure‑as‑code and automated orchestration
• Take POCs through to production with clean, well‑tested code and strong CI/CD practices

Skills and Experience

• Proven experience building production systems and taking POCs into production
• Strong Python skills, with hands‑on experience using common ML and data libraries
• Solid understanding of the end‑to‑end ML lifecycle
• Experience building APIs, CI/CD pipelines, testing and deployment automation
• Public cloud experience and familiarity with IaC tools such as Terraform
• Working knowledge of Docker and Kubernetes
• A product mindset, with a focus on business goals and customer value, not just code
• A curious, pragmatic approach: you fix root causes, document issues and are comfortable saying when you don’t know something

Education

Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Engineering, Applied AI, or a related field (or equivalent practical mastery).

Experience

• 4+ years of related industry experience in machine learning, including hands‑on experience designing, evaluating, and operating LLM‑based or agentic systems
• Strong coding skills in Kotlin and/or Python, with the ability to write performant, production‑quality code and work effectively with AI‑assisted software development practices
• Experience building and operating machine learning systems in production, including the operational practices required to improve system quality, reliability, and cost
• Experience building datasets, evaluations, and benchmarks for systems operating at scale; familiarity with SQL, distributed data processing, and cloud data environments
• A strong ownership mindset and a track record of driving ambiguous technical outcomes from problem definition through delivery and operation
• Strong communication and influencing skills, with the ability to explain ML concepts to diverse audiences and steer technical direction with cross‑functional stakeholders
• Experience leading technical work and coaching engineers in a collaborative team or virtual squad
• A pragmatic, iterative approach that balances a high bar for quality with the value of delivering, learning, and improving

It’s great, but not required, if you have

• Experience fine‑tuning smaller language models
• Experience serving and operating LLMs using technologies such as NVIDIA Triton Inference Server
• Experience applying machine learning to personalisation or context‑aware product experiences
• Experience solving complex problems in enterprise SaaS or similarly large‑scale product environments

Benefits & Perks

Atlassian offers a wide range of perks and benefits designed to support you, your family and to help you engage with your local community. Our offerings include health and wellbeing resources, paid volunteer days, and so much more. To learn more, visit go.atlassian.com/perksandbenefits.

About Atlassian

At Atlassian, we're motivated by a common goal: to unleash the potential of every team. Our software products help teams all over the planet and our solutions are designed for all types of work. Team collaboration through our tools makes what may be impossible alone, possible together.

We believe that the unique contributions of all Atlassians create our success. To ensure that our products and culture continue to incorporate everyone's perspectives and experience, we never discriminate based on race, religion, national origin, gender identity or expression, sexual orientation, age, or marital, veteran, or disability status. All your information will be kept confidential according to EEO guidelines.

To provide you the best experience, we can support with accommodations or adjustments at any stage of the recruitment process. Simply inform our Recruitment team during your conversation with them.

To learn more about our culture and hiring process, visit go.atlassian.com/crh.

In line with local law, identity verification (which may include use of biometric data) is a condition of employment with Atlassian for employment fraud purposes.