Ai/Ml Engineer

OverviewAs an AI/ML Engineer at Pythian, you design, build, and maintain scalable AI/ML pipelines for client and internal use.You deploy and optimize models, including LLMs and Generative AI, across production environments and cloud platforms.You collaborate with data scientists and software engineers to deliver production-ready AI systems, emphasizing performance, cost-efficiency, and maintainability.This role combines hands-on engineering with shaping AI solutions for transformative outcomes within a cloud-focused services company.Compensaciones / Beneficioscompetitive total rewardsremote work optionstraining allowance and professional development dayswellness budgetpaid vacation and sick dayscharitable volunteering dayResponsabilidadesDevelop, deploy, and maintain AI/ML pipelines for internal and client-driven projectsDeploy, manage, and scale AI models (LLMs and custom models) into productionTranslate model prototypes into scalable, production-ready AI systemsOptimize model performance, latency, and cost on cloud platformsIntegrate AI/ML solutions with AWS, GCP, Azure and use Docker/Kubernetes for consistent deploymentApply MLOps practices: CI/CD, model versioning, monitoring, maintenanceCoordinate with software engineers to embed AI capabilities into applications and workflowsStay updated on AI/ML tech, Generative AI, and MLOps deployment strategiesRequisitos principalesBachelor’s or Master’s degree in Computer Science, Engineering, AI or related quantitative field4 to 5 years of experience in ML engineering or ML/AI-focused software development1-3 years experience with ADK or other agentic frameworksStrong Python programming skillsExperience with ML frameworks (TensorFlow, PyTorch, Scikit-learn)Hands-on experience deploying/pre-trained models (LLMs/Generative AI) into productionCloud platform experience (AWS, GCP, Azure) and container orchestration (Docker, Kubernetes)Solid knowledge of Data Engineering, ETL/ELT, and GitExperience with Kubeflow or managed ML toolsExperience building/scaling AI/ML systemsFamiliarity with MLOps practices (monitoring, logging, CI/CD)Strong communication and cross-functional collaboration skillsStrong communicationTeam collaboration across cross-functional teamsProblem-solving orientationPythonTensorFlowPyTorch

Requisitos principalesBachelor’s or Master’s degree in Computer Science, Engineering, AI or related quantitative field 4 to 5 years of experience in ML engineering or ML/AI-focused software development 1-3 years experience with ADK or other agentic frameworks Strong Python programming skills Experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn) Hands-on experience deploying/pre-trained models (LLMs/Generative AI) into production Cloud platform experience (AWS, GCP, Azure) and container orchestration (Docker, Kubernetes) Solid knowledge of Data Engineering, ETL/ELT, and Git Experience with Kubeflow or managed ML tools Experience building/scaling AI/ML systems Familiarity with MLOps practices (monitoring, logging, CI/CD) Strong communication and cross-functional collaboration skills Strong communication Team collaboration across cross-functional teams Problem-solving orientation