AIML Architect
- InfoVision Inc
- 10 - 15 years
- Hyderabad
- 4 months ago
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Job Description
Job Summary:We are seeking an accomplished Machine Learning Architect with 12 to 18 years of experience to lead the design and implementation of robust, scalable, and production-grade ML systems in the financial services domain. The ideal candidate will have deep expertise across the entire ML lifecycle from data ingestion and modeling to deployment, serving, and operationalization and a strong understanding of enterprise-level architecture and compliance considerations in the financial industry.
As an ML Architect, you will work cross-functionally with engineering, data science, product, and compliance teams to design end-to-end machine learning platforms and pipelines that power intelligent financial applications, such as fraud detection, credit scoring, customer analytics, and risk management.
Required Qualifications:- 12 to 18 years of experience in software engineering, machine learning, or data platform architecture, with at least 5 years in architecting end-to-end ML solutions.
- Proven experience in the financial domain, working with use cases such as fraud detection, risk scoring, AML, churn prediction, or credit modeling.
- Deep knowledge of computer science fundamentals, including:
- Data structures and algorithms
- Distributed systems
- High-availability and low-latency system design
- Strong programming and architectural experience with Python, and at least one of Java/Scala/C++.
- Expertise in ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and MLOps platforms (e.g., MLflow, Kubeflow, SageMaker, Vertex AI).
- Experience building and deploying RESTful APIs or microservices to serve ML models.
- Solid hands-on experience with data processing tools (e.g., Apache Spark, Kafka, Airflow) and cloud infrastructure (AWS/GCP/Azure).
- Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes) for deploying scalable systems.
- Prior experience in ML architecture within financial institutions, fintech, or regulatory environments.
- Working knowledge of governance and compliance frameworks: model auditability, explainable AI (XAI), fairness and bias detection.
- Experience designing real-time inference and streaming-based ML systems.
- Understanding of feature stores, model registries, and data lineage in ML pipelines.
- Strong communication and leadership skills, capable of influencing C-level stakeholders and guiding engineering decisions across departments.
Technical Skills
12+ years of experience in IT and relevant Machine learning experience
Strong understanding of software engineering principles and fundamentals including data structures and algorithms.
Excellent understanding of object-oriented concepts and Python. Strong knowledge of computer science fundamentals to develop a scalable system Experience in NLP models like BERT, Transformer architectures, etc.
Experience in leveraging Computer Vision and OCR in document extraction use cases
Familiarity with ML problems (ex, Classification/Regression/Anomaly Detection) Python ML Packages (Scikit/Numpy/Pandas/OpenCV) Exposure to REST API/ Flask concepts
Experience in deep learning package, Pytorch, Tensorflow etc Familiarity with Graph database like Neo4j will be a plus.
Roles and Responsibilities
- Architect and design scalable ML systems that cover the entire lifecycle:
- Data acquisition and preprocessing
- Model training, validation, and optimization
- Model deployment and API serving
- Model monitoring, drift detection, retraining, and governance
- Build and maintain modular, reusable, and compliant ML platforms and services, ensuring scalability, reliability, and performance for production environments.
- Define architecture and best practices for:
- Model versioning and reproducibility
- Feature engineering and feature stores
- MLOps workflows (CI/CD pipelines, model registry, deployment automation)
- Collaborate with data engineers, ML engineers, software architects, and domain experts to align technical design with business goals and regulatory requirements.
- Ensure systems meet financial industry standards for data privacy, explainability, auditability, and regulatory compliance (e.g., model risk management frameworks).
- Mentor engineering and data science teams on architectural patterns, system design principles, and ML operationalization.
- Evaluate and integrate new technologies and tools in ML infrastructure and cloud platforms.
Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: Engineering - Software & QARole Category: Software DevelopmentRole: Technical ArchitectEmployement Type: Full timeContact Details:
Company: InfoVision IncLocation(s): Hyderabad
Keyskills: fundamentals algorithms rest python c++ scala data processing distribution system machine learning tools microservices java framework computer science leadership data structures software engineering finance programming ml communication skills architecture object
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