Roles
Machine Learning Engineer
Machine Learning Engineer

Machine Learning Engineer

Develop and deploy advanced algorithms that enable machines to learn and make predictions.

Overview
Tests
Advanced Analytics
Job Family
AU$150k
Salary
Average salary in Australia
19%
Job Growth
The number of positions relative to last year
45
Open Roles
Job openings on Alooba Jobs

Machine Learning Engineers specialize in designing and implementing machine learning models to solve complex problems across various industries. They work on the full lifecycle of machine learning systems, from data gathering and preprocessing to model development, evaluation, and deployment. These engineers possess a strong foundation in AI/ML technology, software development, and data engineering. Their role often involves collaboration with data scientists, engineers, and product managers to integrate AI solutions into products and services.

What are the responsibilities & duties of a Machine Learning Engineer?

  • Lead the end-to-end lifecycle of machine learning systems, from experimentation to deployment and performance monitoring.
  • Design and implement machine learning solutions for various applications like object detection, semantic segmentation, and reinforcement learning.
  • Collaborate with cross-functional teams to understand business needs and develop tailored machine learning solutions.
  • Stay up-to-date with the latest machine learning research and trends, and apply this knowledge to improve existing models and systems.
  • Mentor and provide technical guidance to junior team members, fostering skill development within the team.
  • Optimize and fine-tune machine learning algorithms for improved performance and scalability.
  • Participate in code reviews and contribute to the continuous improvement of model development practices.
  • Collaborate closely with data scientists and engineers in building and maintaining data pipelines and infrastructure.
  • Analyze algorithmic performances, identify common issues, and propose innovative solutions for improvement.
  • Take a lead role in data collection, feature engineering, and data preprocessing for model training.

What are the required skills & experiences of a Machine Learning Engineer?

  • Master or PhD in Computer Science, Mathematics, Data Science, or a related field.
  • Proven expertise in AI/ML technologies, including deep learning, NLP, and unsupervised learning.
  • Experience in developing and deploying large-scale machine learning models in production environments.
  • Strong programming skills in languages such as Python, Java, or Scala, and familiarity with ML libraries like TensorFlow or PyTorch.
  • Deep knowledge of data and machine learning pipelines using tools like Scikit-learn, Spark ML, or OpenCV.
  • Proficiency in SQL and data query languages, and experience with cloud solutions such as AWS or Google Cloud.
  • Strong problem-solving skills and ability to translate complex technical concepts into actionable insights.
  • Experience in software development and familiarity with software engineering best practices.
  • Good understanding of model evaluation, validation, and optimization techniques.
  • Excellent communication skills, capable of articulating technical concepts to both technical and non-technical audiences.

Discover how Alooba can help identify the best Machine Learning Engineers for your team

Machine Learning Engineer Levels

Intern Machine Learning Engineer

Intern Machine Learning Engineer

An Intern Machine Learning Engineer is an entry-level professional who assists in designing and implementing machine learning models. They work under the guidance of experienced engineers, leveraging their academic knowledge to solve real-world problems. Their role is vital in supporting the development and optimization of machine learning algorithms and systems.

Graduate Machine Learning Engineer

Graduate Machine Learning Engineer

A Graduate Machine Learning Engineer is an enthusiastic professional who applies their foundational knowledge in machine learning, algorithms, and programming to develop models and systems. They are data-driven, curious, and ready to contribute to machine learning projects under the guidance of senior engineers.

Junior Machine Learning Engineer

Junior Machine Learning Engineer

A Junior Machine Learning Engineer is an emerging professional who applies machine learning models to solve complex problems. They work under the guidance of senior engineers to develop, test, and improve machine learning algorithms. Their role is crucial in helping organizations leverage artificial intelligence to drive innovation and efficiency.

Machine Learning Engineer (Mid-Level)

Machine Learning Engineer (Mid-Level)

A Mid-Level Machine Learning Engineer applies their knowledge of machine learning algorithms and computational principles to develop models that enable the extraction of valuable insights from data. They are proficient in programming languages, data structures, and have a strong understanding of both software development and data science principles.

Senior Machine Learning Engineer

Senior Machine Learning Engineer

A Senior Machine Learning Engineer is a seasoned professional who specializes in designing, developing, and deploying machine learning models. They leverage advanced computational skills to create algorithms that can learn from and make decisions based on data, driving innovation and business growth.

Lead Machine Learning Engineer

Lead Machine Learning Engineer

A Lead Machine Learning Engineer is a seasoned professional who leverages their expertise in machine learning, data analysis, and software engineering to develop predictive models and algorithms that drive business intelligence. They lead teams, guide project direction, and innovate in the field of machine learning to elevate organizational success.

Common Machine Learning Engineer Required Skills

AccessibilityAccessibilityActivation FunctionsActivation FunctionsAdaptabilityAdaptabilityAdobe AnalyticsAdobe AnalyticsAdobe PhotoshopAdobe PhotoshopAdobe TargetAdobe TargetAgileAgileAlgorithmsAlgorithmsAmazon GlueAmazon GlueAmazon Web ServicesAmazon Web ServicesAnalytics EngineeringAnalytics EngineeringAnalytics ProgrammingAnalytics ProgrammingApache AirflowApache AirflowApache BeamApache BeamApache CassandraApache CassandraApache FlinkApache FlinkApache HadoopApache HadoopApache HiveApache HiveApache IcebergApache IcebergApache ImpalaApache ImpalaApache NiFiApache NiFiApache SparkApache SparkAPIsAPIsApplication Scaling StrategiesApplication Scaling StrategiesArtificial IntelligenceArtificial IntelligenceArtificial Intelligence EngineeringArtificial Intelligence EngineeringArtificial Neural NetworksArtificial Neural NetworksAssertivenessAssertivenessAutocorrelationAutocorrelationAutomated TestingAutomated TestingAutomationAutomationAutoMLAutoMLAWS LambdaAWS LambdaAzureAzureAzure Data FactoryAzure Data FactoryAzure Data LakeAzure Data LakeAzure DatabricksAzure DatabricksBack-End DevelopmentBack-End DevelopmentBackpropagationBackpropagationBaggingBaggingBalancing TreesBalancing TreesBar ChartsBar Charts
Bard
BardBashBashBatch NormalizationBatch NormalizationBayes TheoremBayes TheoremBayesian AnalysisBayesian AnalysisBehavioral AnalyticsBehavioral Analytics
BERT
BERTBig DataBig DataBig Data MiningBig Data MiningBinary TreesBinary TreesBlind-spot BiasBlind-spot BiasBoostingBoostingBranchingBranchingCachingCachingCaffeCaffeCaretCaretCausal InferenceCausal InferenceCausationCausationCentral Limit TheoremCentral Limit TheoremChart InterpretationChart InterpretationChatbotsChatbotsChatGPTChatGPTChi-Squared DistributionChi-Squared DistributionCI/CDCI/CDClass RepresentationClass RepresentationClassesClassesClassification Loss FunctionsClassification Loss FunctionsClassification ModelsClassification ModelsClojureClojureCloud ArchitectureCloud Architecture
Cloud Composer
Cloud ComposerCloud ComputingCloud ComputingCloud Data EngineeringCloud Data EngineeringCloud MonitoringCloud MonitoringCloudera Data PlatformCloudera Data PlatformCode ReviewsCode ReviewsCognitive BiasesCognitive BiasesCognitive ComputingCognitive ComputingCollectionsCollectionsCollectorsCollectorsColumnar DatabasesColumnar DatabasesCommand Line ScriptingCommand Line ScriptingCommittingCommittingComplexityComplexityComputer ScienceComputer ScienceComputer VisionComputer VisionConcurrency ControlConcurrency ControlConcurrency ControlsConcurrency ControlsConditional OperatorsConditional OperatorsConditional ProbabilityConditional ProbabilityConfidence IntervalsConfidence IntervalsConfusion MatricesConfusion MatricesConscientiousnessConscientiousnessContainerizationContainerizationContent GenerationContent GenerationContinuous LearningContinuous LearningConversational AIsConversational AIsConvolutionConvolutionConvolution MatricesConvolution MatricesConvolutional Neural NetworksConvolutional Neural NetworksCost FunctionsCost FunctionsCQRSCQRSCrazy EggCrazy EggCreativityCreativitycroncronCross Site ScriptingCross Site ScriptingCross ValidationCross ValidationCustomer InsightsCustomer InsightsData AnalysisData AnalysisData ArchitectureData ArchitectureData EngineeringData EngineeringData Engineering InfrastructureData Engineering InfrastructureData FabricData FabricData FormatsData FormatsData GovernanceData GovernanceData InfrastructureData InfrastructureData IntegrationData IntegrationData LakehouseData LakehouseData LeakageData LeakageData ManipulationData ManipulationData MaskingData MaskingData ModellingData ModellingData Pipeline OrchestrationData Pipeline OrchestrationData PipelinesData PipelinesData ScienceData ScienceData SplittingData SplittingData Storage FrameworkData Storage FrameworkData StoresData StoresData StorytellingData StorytellingData StructuresData StructuresData TransferData TransferData TransformationsData TransformationsData VisualizationData VisualizationData-Driven Decision MakingData-Driven Decision MakingDatabase DesignDatabase DesignDatabase ModelingDatabase ModelingDatabase MonitoringDatabase MonitoringDatabase Performance OptimisationDatabase Performance OptimisationDatabase Scaling StrategiesDatabase Scaling StrategiesDatabricksDatabricksDatadogDatadog
Dataflow
DataflowDataFramesDataFramesDataOpsDataOpsDAXDAXdbtdbtDebuggingDebuggingDeep LearningDeep LearningDeep Learning EngineeringDeep Learning EngineeringDenial of ServiceDenial of ServiceDependency GraphsDependency GraphsDependency InversionDependency InversionDesign PatternsDesign PatternsDesign ThinkingDesign ThinkingDeveloper PlatformsDeveloper PlatformsDevOpsDevOpsDimensional ModellingDimensional ModellingDimensionality ReductionDimensionality ReductionDisplay MarketingDisplay MarketingDistance MatricesDistance MatricesDistance MeasuresDistance MeasuresDistance MetricsDistance MetricsDistributed Data ProcessingDistributed Data ProcessingDistributed SQL Query EngineDistributed SQL Query EngineDistributionsDistributionsDo-While LoopsDo-While LoopsDockerDockerDynamic ProgrammingDynamic ProgrammingEdge AIEdge AIElasticsearchElasticsearchElixirElixirEncapsulationEncapsulationEnglish GrammarEnglish GrammarEnsemble MethodsEnsemble MethodsEntropyEntropyError MetricsError MetricsError of DecompositionError of DecompositionETL/ELT ProcessesETL/ELT ProcessesEvaluation MetricsEvaluation MetricsEvaluation StrategiesEvaluation StrategiesEvent Data AnalysisEvent Data AnalysisEvent Driven ArchitectureEvent Driven ArchitectureEvent StreamingEvent StreamingExploratory Data AnalysisExploratory Data AnalysisExtreme ProgrammingExtreme ProgrammingFact TablesFact TablesFeature DependenciesFeature DependenciesFeature EngineeringFeature EngineeringFew-Shot PromptingFew-Shot PromptingFFTFFTFinancial ModelingFinancial ModelingFitting AlgorithmsFitting AlgorithmsFivetranFivetranFor LoopsFor LoopsForeach LoopsForeach LoopsForecastingForecastingForkingForkingFormulasFormulasFunctional ProgrammingFunctional ProgrammingFunctional RequirementsFunctional RequirementsFunctionsFunctionsGaussian Mixture ModelsGaussian Mixture ModelsGenerative Adversarial NetworksGenerative Adversarial NetworksGenerative AIGenerative AIGenerative ModelsGenerative ModelsGenetic AlgorithmsGenetic AlgorithmsGitGitGitHubGitHubGoGo
Google BigQuery
Google BigQuery
Google Cloud Platform
Google Cloud PlatformGPTGPTGradient BoostingGradient BoostingGradient DescentGradient DescentGradientsGradientsGraph AnalyticsGraph AnalyticsGraph TheoryGraph TheoryGraphQLGraphQLGraphsGraphsHadoop Distributed File SystemHadoop Distributed File SystemHaskellHaskellHeteroscedasticityHeteroscedasticityHistogramsHistogramsHMMHMMHomoscedasticityHomoscedasticityHTTP MethodsHTTP MethodsIBM Db2IBM Db2IDEIDEIgnoringIgnoringImputationImputationInductive ReasoningInductive ReasoningInformaticaInformaticaInfrastructure as CodeInfrastructure as CodeInterface Segregation PrincipleInterface Segregation PrincipleInternet SecurityInternet SecurityJavaJavaJSONJSONJupyter NotebookJupyter NotebookK-MeansK-MeansKerasKerasKeysKeysKNIMEKNIMEKNNKNNKnowledge GraphsKnowledge GraphsKotlinKotlinKubeflowKubeflowKubernetesKubernetesLanguage ModelingLanguage ModelingLeadershipLeadershipLFSLFSLiftLiftLinear ModellingLinear ModellingLinear RegressionLinear RegressionLinked ListsLinked ListsLinuxLinuxLiskov Substitution PrincipleLiskov Substitution PrincipleLispLispListsListsLLMsLLMsLogistic RegressionsLogistic RegressionsLoopsLoopsLoss FunctionsLoss FunctionsLSILSILuaLuaMachine LearningMachine LearningMachine Learning EngineeringMachine Learning EngineeringMapReduceMapReduceMariaDBMariaDBMarkdownMarkdownMATLABMATLABMatricesMatricesMatrix DecompositionMatrix DecompositionMax PoolingMax PoolingMean Squared ErrorMean Squared ErrorMercurialMercurialMergingMergingMerging MethodsMerging MethodsMethodologiesMethodologiesMetricsMetricsMicroservicesMicroservicesMicrosoft AdvertisingMicrosoft AdvertisingMissing Value TreatmentMissing Value TreatmentMLflowMLflowMode AnalyticsMode AnalyticsModel BiasModel BiasModel EvaluationModel EvaluationModel ExplanationModel ExplanationModel InterpretabilityModel InterpretabilityModel MetricsModel MetricsModel MonitoringModel MonitoringModel Performance MetricsModel Performance MetricsModel TrainingModel TrainingModel ValidationModel ValidationModel VarianceModel VarianceModelsModelsMoving AveragesMoving AveragesMulti-threadingMulti-threadingMulticollinearityMulticollinearityMultilayer PerceptronMultilayer PerceptronMVCMVCNaive BayesNaive BayesNeural Network ArchitectureNeural Network ArchitectureNeural NetworksNeural NetworksNeuroticismNeuroticismNode.jsNode.jsNormal DistributionNormal DistributionNormalizationNormalizationNumPyNumPyObject-Oriented ProgrammingObject-Oriented ProgrammingOne-Hot EncodingOne-Hot EncodingOperating SystemsOperating SystemsOptimizationOptimizationORMORMOutlier RemovalOutlier RemovalOutlier TreatmentOutlier TreatmentOverfittingOverfittingParallel Computing FrameworkParallel Computing FrameworkParameter TuningParameter TuningPartitioningPartitioningPHPPHPPlotlyPlotlyPolymorphismPolymorphismPre-processingPre-processingPresentationsPresentationsProgrammingProgrammingProgramming ArchitecturesProgramming ArchitecturesProgramming ConceptsProgramming ConceptsPub/SubPub/SubPythonPythonPyTorchPyTorchQuboleQuboleQuery Execution PlansQuery Execution PlansQuery OptimisationQuery OptimisationQueuesQueuesRandom ForestRandom ForestRandom Number GenerationRandom Number GenerationRate LimitingRate LimitingRecommendation SystemsRecommendation SystemsRecurrent Neural NetworkRecurrent Neural NetworkRecursionRecursionRedisRedisRedshiftRedshiftReduxReduxRegression ModelsRegression ModelsRegressionsRegressionsRegularizationRegularizationReinforcement LearningReinforcement LearningRelational Data ModelsRelational Data ModelsRemote RepositoriesRemote RepositoriesRequirements GatheringRequirements GatheringRequirements TranslationRequirements TranslationREST ArchitectureREST ArchitectureRFM AnalysisRFM AnalysisRidge RegressionRidge RegressionRoboticsRoboticsRobustnessRobustnessROCROCRShinyRShinyRudderStackRudderStackS3S3SAP Data ServicesSAP Data ServicesScalaScalaScikit-learnScikit-learnSearching ArraysSearching ArraysSecure ProgrammingSecure ProgrammingSemi-supervised learningSemi-supervised learningServerless Architectures in DataServerless Architectures in DataServerless ComputingServerless ComputingSGDSGDSignal to NoiseSignal to NoiseSimilarity FunctionsSimilarity FunctionsSimulation ModelingSimulation ModelingSingle Responsibility PrincipleSingle Responsibility PrincipleSnapLogicSnapLogicSnowflake Data CloudSnowflake Data CloudSOAPSOAPSocial Media AnalyticsSocial Media AnalyticsSoftware Development Life CycleSoftware Development Life CycleSolution DesignSolution DesignSourcetreeSourcetreeSpatial ReasoningSpatial ReasoningSpeech RecognitionSpeech RecognitionSplunkSplunkStandard DeviationStandard DeviationStandardizationStandardizationStatistical MeasuresStatistical MeasuresStrategies for Missing DataStrategies for Missing DataStreamsStreamsStructured DataStructured DataSupervised LearningSupervised LearningSVMSVMSyntaxSyntaxSynthetic Data GenerationSynthetic Data GenerationSystems ArchitectureSystems ArchitectureT-ScoresT-ScoresT-TestsT-TestsTablesTablesTask SchedulingTask SchedulingTensorFlowTensorFlowTerraformTerraformTest EnvironmentTest EnvironmentTheanoTheanoThrottlingThrottlingTime ComplexityTime ComplexityTinybirdTinybirdTransactionsTransactionsTransfer LearningTransfer LearningTransport Layer SecurityTransport Layer SecurityTrinoTrinoType 1 ErrorType 1 ErrorType 2 ErrorType 2 ErrorTypeScriptTypeScriptUnderfittingUnderfittingUnixUnixUnstructured DataUnstructured DataUnsupervised AlgorithmsUnsupervised AlgorithmsUnsupervised LearningUnsupervised LearningUser Behaviour AnalyticsUser Behaviour AnalyticsUser ExperienceUser ExperienceVirusesVirusesVLOOKUPVLOOKUPWeb CrawlingWeb CrawlingWeb ServersWeb ServersWhile LoopWhile LoopWorkflow AutomationWorkflow AutomationWormsWormsXMLXMLYAMLYAMLZ-TestsZ-Tests

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