Machine Learning Engineer
Altis
Senior Machine Learning Engineer
Location: Hybrid, 3 days per week on-site
Language: Strong written and verbal English communication skills
Duration: 6-month contract with the possibility of extension
About the OpportunityAre you a hands-on Machine Learning Engineer who enjoys turning innovative AI solutions into reliable, production-ready systems? This opportunity offers the chance to help a large enterprise organization scale its AI capabilities by building robust deployment frameworks, automation, and monitoring solutions.
Working alongside technical teams and business stakeholders, you'll play a key role in bridging the gap between machine learning experimentation and production. Your expertise will help establish scalable MLOps practices that improve reliability, performance, and the delivery of AI solutions across the organization.
What's In It for YouWork on high-impact AI and machine learning initiatives with enterprise-wide reach.Collaborate with experienced technical professionals in an innovative, team-oriented environment.Gain exposure to modern Azure AI technologies and advanced MLOps practices.Enjoy a hybrid work arrangement with the possibility of a contract extension.
Your ResponsibilitiesYou'll design, develop, deploy, and operationalize machine learning and deep learning models using Azure Machine Learning and Azure AI Foundry.You'll build reusable MLOps pipelines, CI/CD workflows, containerized solutions, APIs, and automation to streamline production deployments.You'll establish monitoring and observability practices to track model performance, identify drift, troubleshoot issues, and support retraining.You'll apply classification, regression, clustering, feature engineering, and hyperparameter tuning techniques to optimize model performance.You'll collaborate with stakeholders to translate business objectives into scalable AI solutions, measurable outcomes, and effective validation strategies.You'll support data preparation, quality assurance, experimentation, and resource planning while managing competing priorities and deadlines.
Skills and QualificationsExtensive hands-on experience in machine learning engineering, including successfully deploying and supporting models in production environments.Advanced expertise in Azure Machine Learning (ML Studio), Microsoft Foundry/Azure AI Foundry, MLOps, CI/CD, containers, APIs, automation, and model observability.Strong programming and technical skills with Python, SQL, Databricks, Power BI, Power Automate, VS Code, Git, and Jira.Deep understanding of machine learning algorithms, statistics, classification, regression, clustering, feature engineering, model evaluation, and hyperparameter optimization.Demonstrated experience with model drift, retraining, performance optimization, production troubleshooting, data validation, and preprocessing.Strong analytical, communication, stakeholder management, and collaboration skills, with the ability to deliver results across competing priorities.
All qualified applicants will receive fair consideration for employment. We welcome individuals of all backgrounds, experiences, and identities including those who identify as women, members of racialized groups, Indigenous Peoples, persons with disabilities, and 2SLGBTQIA+ communities. If you require an accommodation, please review our accessibility policy and reach out to our accessibility officer with any questions. Our human recruiters review all applications and always make the final hiring decision. On occasion, we also use AI‑assisted tools to help review applications.
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Location: Hybrid, 3 days per week on-site
Language: Strong written and verbal English communication skills
Duration: 6-month contract with the possibility of extension
About the OpportunityAre you a hands-on Machine Learning Engineer who enjoys turning innovative AI solutions into reliable, production-ready systems? This opportunity offers the chance to help a large enterprise organization scale its AI capabilities by building robust deployment frameworks, automation, and monitoring solutions.
Working alongside technical teams and business stakeholders, you'll play a key role in bridging the gap between machine learning experimentation and production. Your expertise will help establish scalable MLOps practices that improve reliability, performance, and the delivery of AI solutions across the organization.
What's In It for YouWork on high-impact AI and machine learning initiatives with enterprise-wide reach.Collaborate with experienced technical professionals in an innovative, team-oriented environment.Gain exposure to modern Azure AI technologies and advanced MLOps practices.Enjoy a hybrid work arrangement with the possibility of a contract extension.
Your ResponsibilitiesYou'll design, develop, deploy, and operationalize machine learning and deep learning models using Azure Machine Learning and Azure AI Foundry.You'll build reusable MLOps pipelines, CI/CD workflows, containerized solutions, APIs, and automation to streamline production deployments.You'll establish monitoring and observability practices to track model performance, identify drift, troubleshoot issues, and support retraining.You'll apply classification, regression, clustering, feature engineering, and hyperparameter tuning techniques to optimize model performance.You'll collaborate with stakeholders to translate business objectives into scalable AI solutions, measurable outcomes, and effective validation strategies.You'll support data preparation, quality assurance, experimentation, and resource planning while managing competing priorities and deadlines.
Skills and QualificationsExtensive hands-on experience in machine learning engineering, including successfully deploying and supporting models in production environments.Advanced expertise in Azure Machine Learning (ML Studio), Microsoft Foundry/Azure AI Foundry, MLOps, CI/CD, containers, APIs, automation, and model observability.Strong programming and technical skills with Python, SQL, Databricks, Power BI, Power Automate, VS Code, Git, and Jira.Deep understanding of machine learning algorithms, statistics, classification, regression, clustering, feature engineering, model evaluation, and hyperparameter optimization.Demonstrated experience with model drift, retraining, performance optimization, production troubleshooting, data validation, and preprocessing.Strong analytical, communication, stakeholder management, and collaboration skills, with the ability to deliver results across competing priorities.
All qualified applicants will receive fair consideration for employment. We welcome individuals of all backgrounds, experiences, and identities including those who identify as women, members of racialized groups, Indigenous Peoples, persons with disabilities, and 2SLGBTQIA+ communities. If you require an accommodation, please review our accessibility policy and reach out to our accessibility officer with any questions. Our human recruiters review all applications and always make the final hiring decision. On occasion, we also use AI‑assisted tools to help review applications.
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Vacancy posted 1 hour ago
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