Machine Learning Engineer

Mid or Senior Machine Learning EngineerMust have working rights in AustraliaLocationMelbourne preferred - 2 days a week in the office right by Richmond StationOpen to fully remote Engineers in Australia/New ZealandAbout ProgramaPrograma 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 RoleThis 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 → iterationThis 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 OnYou’ll work closely with Data Scientists, Software Engineers and Product to turn ideas and models into reliable, customer-facing features, such as:Search and retrievalRanking and recommendation systemsSemantic search and embeddingsGenAI and RAGLLM-powered copilotsAgentic workflowsML APIs and servicesProduction ML infrastructureEvaluation and experimentationMonitoring and observabilityYou’ll Probably Enjoy This Role If You…Like owning ML systems beyond the modelling stageWant to understand whether what you build actually creates customer valueEnjoy working across ML, software engineering and infrastructureAre comfortable moving between experimentation and production engineeringThink critically about whether ML is actually the right solution to a problemPrefer pragmatic solutions over unnecessary complexityEnjoy working in a lean environment where you can influence technical directionWant to work on systems used by real customers rather than purely research or internal toolingWhat You’ll Be Responsible ForDesigning, building and shipping end-to-end ML systemsTaking ML solutions from prototype through to productionBuilding and maintaining Python-based services and APIsDeploying and operating ML workloads in AWSImproving model serving, latency, scalability and reliabilityBuilding and improving training and inference pipelinesMonitoring model and system performance in productionDesigning appropriate evaluation frameworks and success metricsRunning offline evaluation and online experimentationWorking with search, ranking and recommendation systemsIdentifying data drift, feature skew, leakage and model degradationContributing to system architecture and technical directionImproving CI/CD and developer workflows around MLWorking with Data Scientists to productionise models and experimentsHelping define which ML or AI problems are actually worth solvingWhat We’re Looking ForMust-haves:4+ years’ experience across Machine Learning Engineering, Software Engineering, Data Engineering or a related fieldCommercial experience building and shipping production ML systemsStrong software engineering fundamentals, including testing, system design and code qualityStrong Python and SQL skills (Experience working with APIs and backend systems)Experience with cloud infrastructure, preferably AWSSolid classical machine learning fundamentals; model selection, training, validation and evaluationUnderstanding of concepts such as: Overfitting, Data leakage, Train/validation/test splits, Precision and recall, Model drift, Feature skew, Offline vs online evaluationExperience monitoring production systems and diagnosing performance or reliability issuesStrong communication and collaboration skillsAbility to work independently and take ownership of ambiguous problemsA product mindset and the ability to connect technical decisions to customer or business outcomesNice to HaveExperience with ranking, recommendation, search and/or retrieval systemsOpenSearch or ElasticsearchVector databases or semantic searchRAG and embedding-based systemsExperience with LLM APIs such as OpenAI, Anthropic or BedrockExperience with agent frameworks or multi-step LLM systemsML orchestration or pipeline tooling such as Kubeflow or similarExperience with Spark or large-scale data processingExperience with Snowflake, dbt, Dagster or modern data-platform toolingExperience with model monitoring and observabilityExperience working in B2B SaaS, startups or scale-upsThis Role Probably Isn’t Right If You…Prefer research or modelling without production ownershipExpect another team to deploy and operate your modelsHave mainly worked in notebooks or experimental environmentsHave only built simple chatbot or LLM-wrapper applicationsPrefer to work in isolation rather than cross-functionallyWant fully defined tasks handed to you before starting workWhy Programa?Work on meaningful AI capabilities embedded directly into a real SaaS productOwn systems from idea through to productionInfluence the technical direction of Programa’s ML platformJoin a well-funded, growing product companyStrong opportunity to have visible impact as Programa continues to scaleFor more info, click apply or contact Georgia@nDeva.com.au