Mid or Senior Machine Learning Engineer
Must have working rights in Australia
Location
Melbourne preferred - 2 days a week in the office right by Richmond Station
Open to fully remote Engineers in Australia/New Zealand
About Programa
Programa is a fast-growing SaaS platform used by architects and interior designers around the world to manage products, projects and workflows in one place.
They're now building the next layer of the platform: AI that helps users make better decisions, find information faster and automate more of their day-to-day work.
To support that growth, Programa is hiring a Mid or Senior Machine Learning Engineer to design, build and operate production ML systems across search, recommendations, GenAI and agentic workflows.
The Role
This role sits at the intersection of Machine Learning and Software Engineering.
Programa is looking for someone with solid classical ML fundamentals who also enjoys the engineering required to take ML systems all the way into production.
You'll work across the full lifecycle:
problem definition - experimentation - production - monitoring - iteration
This is not a research-only role, and it is not a pure MLOps position.
You'll be expected to contribute to the modelling and system design, while also owning the infrastructure, deployment, reliability and performance required to make those systems work for real customers.
What You'll Work On
You'll work closely with Data Scientists, Software Engineers and Product to turn ideas and models into reliable, customer-facing features, such as:
Search and retrieval
Ranking and recommendation systems
Semantic search and embeddings
GenAI and RAG
LLM-powered copilots
Agentic workflows
ML APIs and services
Production ML infrastructure
Evaluation and experimentation
Monitoring and observability
You'll Probably Enjoy This Role If You...
Like owning ML systems beyond the modelling stage
Want to understand whether what you build actually creates customer value
Enjoy working across ML, software engineering and infrastructure




Are comfortable moving between experimentation and production engineering
Think critically about whether ML is actually the right solution to a problem
Prefer pragmatic solutions over unnecessary complexity
Enjoy working in a lean environment where you can influence technical direction
Want to work on systems used by real customers rather than purely research or internal tooling
What You'll Be Responsible For
Designing, building and shipping end-to-end ML systems
Taking ML solutions from prototype through to production
Building and maintaining Python-based services and APIs
Deploying and operating ML workloads in AWS
Improving model serving, latency, scalability and reliability
Building and improving training and inference pipelines
Monitoring model and system performance in production
Designing appropriate evaluation frameworks and success metrics
Running offline evaluation and online experimentation
Working with search, ranking and recommendation systems
Identifying data drift, feature skew, leakage and model degradation
Contributing to system architecture and technical direction
Improving CI/CD and developer workflows around ML
Working with Data Scientists to productionise models and experiments
Helping define which ML or AI problems are actually worth solving
What We're Looking For
Must-haves:
4+ years' experience across Machine Learning Engineering, Software Engineering, Data Engineering or a related field
Commercial experience building and shipping production ML systems
Strong software engineering fundamentals, including testing, system design and code quality
Strong Python and SQL skills (Experience working with APIs and backend systems)




Experience with cloud infrastructure, preferably AWS
Solid classical machine learning fundamentals; model selection, training, validation and evaluation
Understanding of concepts such as: Overfitting, Data leakage, Train/validation/test splits, Precision and recall, Model drift, Feature skew, Offline vs online evaluation
Experience monitoring production systems and diagnosing performance or reliability issues
Strong communication and collaboration skills
Ability to work independently and take ownership of ambiguous problems
A product mindset and the ability to connect technical decisions to customer or business outcomes
Nice to Have
Experience with ranking, recommendation, search and/or retrieval systems
OpenSearch or Elasticsearch
Vector databases or semantic search
RAG and embedding-based systems
Experience with LLM APIs such as OpenAI, Anthropic or Bedrock
Experience with agent frameworks or multi-step LLM systems
ML orchestration or pipeline tooling such as Kubeflow or similar
Experience with Spark or large-scale data processing
Experience with Snowflake, dbt, Dagster or modern data-platform tooling
Experience with model monitoring and observability
Experience working in B2B SaaS, startups or scale-ups
This Role Probably Isn't Right If You...
Prefer research or modelling without production ownership
Expect another team to deploy and operate your models
Have mainly worked in notebooks or experimental environments
Have only built simple chatbot or LLM-wrapper applications
Prefer to work in isolation rather than cross-functionally
Want fully defined tasks handed to you before starting work
Why Programa?
Work on meaningful AI capabilities embedded directly into a real SaaS product
Own systems from idea through to production
Influence the technical direction of Programa's ML platform
Join a well-funded, growing product company
Strong opportunity to have visible impact as Programa continues to scale
#J-*****-Ljbffr

📌 Machine Learning Engineer (Melbourne)
🏢 Programa
📍 Melbourne