Biz2X
Website:
biz2x.com
Job details:
Roles and Responsibilities:
3 – 5 years of product development experience for large scale systems with high volume and high-performance requirements.
About the Role
AI Engineer with a blend of AI deployment, MLOps, software integration, and AI infrastructure skills, the ideal candidate should have:
Responsibilities
- Strong AI/ML Engineering Skills
- Hands-on experience in model deployment, integration, optimization, and serving AI models in production.
- Ability to integrate AI models into lending workflows and APIs.
- Expertise in LLM prompt engineering, calling tools, RAG, and structured outputs.
- Implement hallucination minimization techniques and create continuous feedback loops for model improvement.
- ML Ops & Cloud Deployment Expertise
- Knowledge of CI/CD pipelines for AI models.
- Knowledge in containerization (Docker, Kubernetes).
- Knowledge of security and compliance.
- Implement AI guardrails, secure data protection protocols, and ensure compliance with financial data standards.
- Knowledge of cloud-based AI services (AWS).
- AI Software & API Integration
- Expert in Python / TypeScript programming.
- Building APIs to serve AI models in real-time decision-making for lending and risk assessment.
- Experience with serverless AI architectures and event-driven workflows.
- Experience with Vector DB and RDBMS / NoSQL.
- AI Infrastructure & Scaling
- Knowledge of AI workloads efficiently, optimizing for low latency and high availability.
- Experience with GPU acceleration and distributed computing frameworks.
Qualifications
- Preferably from a product-based company.
- Minimum 60% throughout academics, including highest qualification.
Required Skills
- Strong programming skills in Python / TypeScript, and API development.
- Hands-on experience with MLOps tools, containerization, and cloud platforms.
- Knowledge of AI model deployment, scaling, and performance optimization.
Preferred Skills
- Experience with AI model deployment, scaling, and performance optimization.
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