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 strong 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
For more info, click apply or contact [email protected]