Ai Systems Developer

Há 7 dias

Cachoeirinha, Brasil Bebeeartificialintelligence Tempo inteiro

Job OverviewWe are seeking a highly skilled AI Systems Developer to join our team.As an AI Systems Developer, you will be responsible for designing, building, and deploying scalable machine learning systems and end-to-end pipelines on AWS.Key ResponsibilitiesDesign and develop production-ready machine learning systems and end-to-end pipelines using AWS services.Partner with data scientists, software engineers, and product teams to define requirements, select algorithms, and deliver impactful ML solutions.Architect, optimize, and maintain ML infrastructure, including data ingestion, model training, deployment, serving, monitoring, and lifecycle management.Lead the data preparation and feature engineering process to ensure data quality, integrity, and scalability across large datasets.Implement and optimize machine learning models, focusing on performance, accuracy, and reliability.Build and manage robust data pipelines and orchestration workflows to support machine learning systems at scale.Integrate models into backend services and APIs for seamless interaction with applications and end users.Contribute to MLOps practices, including CI/CD for ML, model registries, experiment tracking, automated retraining, and infrastructure-as-code provisioning.Utilize Infrastructure-as-Code tools like Terraform, AWS CDK, or CloudFormation to build and maintain scalable, secure ML infrastructure.Stay up-to-date with emerging trends in AI/ML and evaluate new research, frameworks, and tools to enhance product capabilities.Provide technical leadership and mentorship to junior engineers, guiding best practices throughout the ML lifecycle.Requirements7+ years of professional experience designing, building, and deploying machine learning models in production environments.Expert proficiency in Python and machine learning frameworks like TensorFlow, PyTorch, and scikit-learn.Proficiency with TypeScript for building ML-integrated backend services and automation workflows.Experience with Infrastructure-as-Code tools (Terraform, AWS CDK, or CloudFormation) for deploying ML infrastructure.Strong knowledge of data processing and analysis tools (Pandas, NumPy, SQL) and orchestration workflows.Proven track record deploying machine learning systems into production and integrating them into real products or services at scale.Experience with containerization (Docker), orchestration (Kubernetes), and MLOps best practices.Preferred QualificationsExperience with large language models (LLMs), retrieval-augmented generation (RAG) pipelines, or agentic AI systems.Expertise in deep learning, NLP, time-series forecasting, or computer vision.Familiarity with platforms like MLflow, Kubeflow, or Amazon SageMaker for model lifecycle management.Contributions to open-source AI/ML projects or publications in the field.BenefitsWellbeing SupportMacbook Purchase Support

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