Senior Machine Learning Engineer

Overview
Mutinex Sydney, New South Wales, Australia
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. Mutinex is on a mission to build a universal business growth decision engine that 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 excellence 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
Internal Tool & Platform Development:
Architect, build, and evolve the high-performing internal tools and platforms that automate and scale our data and modelling pipelines.
LLM-Integrated ML Operations:
Design and implement LLM-powered automation for ML pipeline optimisation, including intelligent parameter tuning, automated model selection, and agentic workflows that reduce manual intervention while maintaining high model quality and reliability.
ML Governance & Trust Frameworks:
Build comprehensive machine learning training and validation frameworks that ensure model reliability, interpretability, and compliance, that build trust with customers through transparent model quality assurance.
Embedded Quality & Observability:
Go beyond simple data validation. Design and implement robust, automated frameworks for data quality assurance, error handling, and end-to-end observability across our data platform.
Performance Optimisation:
Proactively identify and eliminate performance bottlenecks across the platform, from data ingestion and transformation to our large-scale modelling pipelines.
Collaboration and Mentorship:
Work effectively within a cross-functional team, collaborating with product managers, data scientists, and other engineers. Share your expertise and guide team members, fostering their growth and development.
What We\'re Looking For
Software Engineer:
You have experience building and maintaining production-grade systems and know how to take a POC to production.
Experience Building Data-Intensive Applications:
You have a proven track record of designing, building, and scaling complex, data-intensive systems in the cloud. You understand the unique challenges of distributed systems, concurrency, and handling large data volumes.
Modern Tech Stack:
You have strong Python skills and hands-on experience with modern machine learning frameworks such as scikit-learn, pandas, PyTorch, and TensorFlow. You\'re well-versed in CI/CD workflows, testing frameworks, and deployment automation. You bring solid software engineering practices to the data domain, including principles like SOLID, design patterns, and writing clean, testable, and maintainable code. You also have practical experience with modern cloud infrastructure (we use GCP), infrastructure-as-code tools like Pulumi or Terraform, and containerisation technologies like Docker and Kubernetes.
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:
You understand the importance of aligning technical solutions with business goals and user needs. You\'re able to think beyond the code and consider how your work impacts the overall product experience and delivers value to 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 directly affects model quality and customer satisfaction
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 organization
Team
: Work alongside experienced data scientists and engineers who are passionate about reliability and automation
ESOP
: All staff receive equity (ESOP)
Parental Leave
: We offer 12 weeks paid leave to primary parent and 6 weeks to secondary parent 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
Ready to join us?
If you\'re passionate about building data platforms and eager to make a big impact in a fast-growing startup, we\'d love to hear from you. Send us your resume and a brief cover letter explaining why you\'re excited about this opportunity.
Seniority level
Mid-Senior level
Employment type
Full-time
Job function
Software Development
Industries
Software Development and Marketing Services
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