AI/ML Architect, Java Architect / Solution Architect

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October 15

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Indium

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Artificial Intelligence • Engineering • Digital Engineering

Indium is a fast-growing, AI-driven digital engineering services company, developing cutting-edge solutions across applications and data. They specialize in areas such as product engineering, intelligent automation, data analytics, and quality engineering, catering to various industries including BFSI and healthcare. Indium focuses on delivering customer-centric experiences and innovative solutions to enhance business processes and drive digital transformation.

1001 - 5000 employees

🤖 Artificial Intelligence

💰 $1M Venture Round on 2006-04

📋 Description

• 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

🎯 Requirements

• 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)

🏖️ Benefits

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