AI/ML Architect, Java Architect / Solution Architect

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🕒 Outubro 15, 2025

🇺🇸 Estados Unidos – Remoto (EUA)

⏰ Tempo Integral

🟡 Pleno

🟠 Sênior

💻 Engenheiro de Soluções

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Indium

SiteLinkedInTodas as Vagas

1001 - 5000 funcionários

🤖 Inteligência Artificial

💰 $1.000.000 Venture Round em 2006-04

Artificial Intelligence • Engineering • Digital Engineering

A Indium é uma empresa de serviços de engenharia digital em rápido crescimento, impulsionada por IA, desenvolvendo soluções inovadoras em aplicações e dados. Ela se especializa em áreas como engenharia de produtos, automação inteligente, análise de dados e engenharia de qualidade, atendendo a diversas indústrias, incluindo BFSI e saúde. A Indium foca em oferecer experiências centradas no cliente e soluções inovadoras para aprimorar processos de negócios e impulsionar a transformação digital.

Descrição

• Design and review machine learning architecture pipelines end-to-end • Architect scalable models using tools like TensorFlow, PyTorch, Scikit-learn • Drive data strategy, feature stores, model lifecycle (training, deployment, monitoring) • Collaborate with data engineering and product teams to align technical goals • Define standards for MLOps, model governance, and responsible AI • Own the technical design for backend systems built on Java / Spring Boot • Create solution blueprints, architecture documents, and design patterns • Guide teams on microservices, containerization, API design, and DevOps • Conduct code reviews, architecture assessments, and risk mitigation • Collaborate with product and infrastructure teams for seamless delivery • Analyze requirements and design technical solutions across platforms • Create architecture roadmaps for applications, integrations, and cloud infrastructure • Lead POCs, architecture evaluations, and tech selection • Act as a technical bridge between stakeholders, developers, and leadership

🎯 Requisitos

• 8+ years in ML/DL, data science, or AI-related roles • Expertise in Python, ML frameworks, distributed computing (Spark, Dask) • Cloud-native ML deployment on AWS SageMaker, Azure ML, GCP Vertex AI • Knowledge of Kubeflow, MLFlow, Airflow, Docker/K8s for ML pipelines • Strong grasp of ML lifecycle management, monitoring, and retraining • Proficiency in Java 11+/Spring Boot, RESTful APIs, ORM frameworks • Experience with Kubernetes, Docker, messaging systems (Kafka, RabbitMQ) • Strong grasp of cloud-native development (AWS, Azure, GCP) • In-depth understanding of microservices, DDD, clean architecture • Performance tuning, scalability, and reliability design • Familiarity with cloud platforms (Azure, AWS, GCP)

🏖️ Benefícios

• Diversity, equity, and inclusion initiatives • WE@IN women empowerment program • Tailored training programs