Machine Learning Engineer

Mutinex; Sydney; Hybrid; AUD 140,000 - 190,000; Full time

Benefits offered by this job

ESOP

Parental Leave

Annual Leave

6 weeks work from anywhere

Job summary

Mutinex is hiring a Machine learning and Software Engineer to design, build, automate, and optimise ML pipelines powering data science workflows. You will work across infrastructure to internal tools, delivering end-to-end solutions in a hybrid environment across Sydney, Melbourne, and New York.

You’ll apply ML lifecycle expertise with Python, APIs, and cloud infrastructure to create reliable, observable, and scalable systems for customers worldwide.

Qualifications

• Experience building production systems and taking POCs to production.
• Skilled in APIs, CI/CD, testing, and deployment automation.
• Familiar with modern cloud infra (GCP), IaC tools like Pulumi or Terraform, and Docker/Kubernetes.
• Solid Python skills with hands-on ML tools: scikit-learn, pandas, PyTorch, TensorFlow.
• Strong craftsmanship: write clean, maintainable, and well-tested code.
• Curiosity and willingness to learn, fill knowledge gaps on the job.
• Startup mindset: align work with business goals and user needs.

Responsibilities

• Predictive Modelling and Forecasting: develop time series models for forecasting and decision support.
• Optimisation Frameworks: build scalable optimisation solving complex constraints for customer decisions.
• Backend API & Database Development: design scalable APIs, databases with FastAPI and SQLAlchemy; ensure CI/CD and clean code.
• Cloud Infrastructure & Orchestration: architect event-driven systems using Cloud Run, Pub/Sub, BigQuery; IaC and automated orchestration.

Skills

Python

ML lifecycle

APIs

CI/CD

Cloud platforms

Curiosity

Product mindset

Proactive problem solving

Tools

FastAPI

SQLAlchemy

Docker

Kubernetes

Pulumi

Terraform

GCP

scikit-learn

pandas

PyTorch

TensorFlow

Job description

We're an early-stage B2B SaaS startup with a proven platform, big-name clients, and millions in revenue. We're not chasing unicorn status; we're building a sustainable, long-lasting business (think Bowhead Whale!). Mutinex is on a mission to build a universal business growth decision engine! It empowers marketing, media, agency, analytics, and finance teams to organise, analyse, and action data at scale, unlocking and optimising the true drivers of sustainable business growth.

We're a hybrid team based in Sydney, Melbourne, and New York. We value communication, open-mindedness, and a culture of feedback.

The Role

We are looking for a Machine learning and Software Engineer to join our team at Mutinex, where you'll be a key contributor to help design, build, automate and optimise the infrastructure and tooling that powers our data science and product workflows.

This is a software engineering role, applied to the data and machine learning domain. This hybrid role combines software engineering skills with machine learning engineering expertise to deliver automated, reliable, and observable ML pipelines that serve our customers globally. You'll have the opportunity to work across our tech stack, from infrastructure to internal tools, to deliver complete, end-to-end solutions.

Role Responsibilities

• Predictive Modelling and Forecasting: Develop and refine time series models to power accurate forecasting and outcome comparisons. Enable data-driven customer decision-making by integrating predictions into planning workflows.
• Optimisation Frameworks: Build and scale optimisation frameworks that solve complex, constraint-based problems to support customer decision making.
• Backend API & Database Development: Design and maintain scalable backend systems. Build APIs and database layers using frameworks like FastAPI and SQLAlchemy. Implement clean, testable code following modern software design principles and CI/CD best practices.
• Cloud Infrastructure & Orchestration: Architect event-driven systems using technologies like Cloud Run, Pub/Sub, and BigQuery. Manage parallel, multi-customer workloads with infrastructure-as-code and automated job orchestration to ensure reliability and scalability.

What We're Looking For

• Software Engineer: You have experience building production systems and taking POCs to production. You're skilled in building APIs, CI/CD, testing, and deployment automation, and you apply solid engineering practices like clean, maintainable code. You’re also familiar with modern cloud infrastructure (we use GCP), IaC tools like Pulumi or Terraform, and container technologies like Docker and Kubernetes.
• Machine Learning & Data-Driven Applications: You have a solid grasp of the machine learning lifecycle, strong Python skills, and hands-on experience with tools like scikit-learn, pandas, PyTorch, and TensorFlow.
• Pragmatic Craftsmanship: You see software engineering as a craft and are passionate about building high-quality, reliable, and well-tested software that has meaningful impact on the business. You don’t just write code that works; you write code that is clean, maintainable, and a pleasure for others to work with.
• Curiosity: You're eager to learn, take on new challenges, and are interested in expanding your technical expertise and impact. You are not afraid to say you don't know and fill any knowledge-gap on the job.
• Product Mindset: As a startup, we look for people who understand and help drive the bigger picture—business goals and user needs. You think beyond coding, focusing on how your work advances the product and creates real value for customers.
• Proactive Problem-Solver: You don't just fix bugs; you identify the root cause and improve the system to prevent future issues. You document past issues and propose clear solutions that go beyond your technical skills.

Why work with us?

• Direct Customer Impact: Your work will directly impact the customer experience and marketing decision making.
• Technical Challenges: Work on cutting-edge ML infrastructure problems at scale
• Autonomy: Lead initiatives from design through implementation with minimal oversight
• Growth: Opportunity to shape ML engineering practices across the organisation
• Team: Work with experienced data scientists and engineers who are driven by impact and committed to doing great work.
• ESOP: All staff receive equity (ESOP)
• Parental Leave: We offer 12 weeks paid leave to primary caregiver and 6 weeks to secondary caregiver after 2 years in business
• Annual Leave: You will receive 20 days base annual leave , +5 days after the first year, and +1 for each year after that up to 30 days total.
• 6 weeks work from anywhere: You are eligible to work 6 weeks anywhere in the world a year - just take your laptop and wifi and you’re good to go!