AI/ML Engineer

Are you an AI/ML Engineer who loves to build and implement innovative solutions that create value at scale? If so, you might be the perfect fit for our Senior AI/ML engineer role at Carlyle.In this role, you will work with data scientists, engineers, and stakeholders to design, deploy, and operationalize state-of-the-art AI/ML systems that solve complex business problems. You will also drive the innovation of MLOps platforms and processes for the full machine learning lifecycle - from model experimentation, to CI/CD pipelines, to model monitoring and retraining in production environments. You will leverage cloud AI/ML platforms, containerization, automation tools and processes to streamline AI/ML workflows.Additionally, you will optimize AI/ML solutions for performance, scalability and cost. You will serve models via microservices, APIs and batch scoring pipelines integrated with data products and business applications.You should have strong expertise in AI/ML platform engineering, modern data platforms, model deployment pipelines, relevant cloud platforms and programming languages like Python. You should also have excellent problem-solving abilities, attention to detail and communication skills.If you are passionate about pushing the boundaries of artificial intelligence and making an impact by delivering innovative ML solutions, this is the role for you. Join us and help shape the future of AI-driven products and services at Carlyle.Primary Responsibilities:Collaborate with stakeholders and data scientists to translate business problems and requirements into ML solutionsEngineer end-to-end AI/ML systems from prototyping to production deploymentDesign and implement AI/ML pipelines for data ingestion, transformation, model training, evaluation, and inferenceChoose and apply suitable ML algorithms and frameworks such as TensorFlow, PyTorch, Keras for model developmentOptimize model performance, accuracy and fairness using techniques like hyperparameter tuning, error analysis, and model governanceDeploy and serve models using REST APIs, serverless functions, or microservicesMonitor and maintain AI/ML solutions using AI/MLOps best practices and toolsEnhance model scalability, performance and cost efficiency using cloud AI/ML platforms, containerization, and automationBuild AI/MLOps discipline and practiceRequirements:Education &CertificatesBachelor’s degree, requiredConcentration in Computer Science, Information Technology, or related field, preferredIndustry Cloud and AI/ML Engineering level certifications desiredProfessional ExperienceMinimum of 6 years of overall relevant technical experience, required5+ years of direct experience in AI/ML engineering projects, preferredExperience with LLM refinement and vector database embeddingsExperience with training, evaluating and deploying deep learning modelsCompetencies & AttributesProficiency with common ML and data platforms such as AzureML, Amazon SageMaker, Databricks, and SnowflakeKnowledge of AI/ML pipelines, AI/MLOps concepts and toolsAbility to build production-grade AI/ML solutions with scalability in mindExperience with MLOps tools and techniques to optimize ML lifecycle managementExperience with ML metadata and artifact tracking platforms such as MLflowExperience containerizing and deploying models and solutions to cloud platforms like Azure or AWSUnderstanding of model governance concepts such model risk analysis, QA, complianceExperience with building ML technical architecture diagrams encompassing data, model building, operationsExperience with operating end-to-end ML platforms supporting analytics and ML teamsExperience with assessing model technical debt, maintaining pipelines, keeping systems up-to-dateExperience with Python for analytics and ML applicationsProficiency with common Python data analysis libraries like NumPy, Pandas, SciPyExperience with common Python ML libraries like Scikit-Learn, TensorFlow, PyTorchExperience with Jupyter Notebooks for ML experimentation and prototypingAbility to transition ML prototypes to production solutionsExperience with Terraform for IaC of ML infrastructure on Azure, AWS cloud platforms.Strong problem solving, analytical and communication skills