Total 5 job vacancies by Novacloud Systems Pte. Ltd.

Responsibilities

• Design and develop AI/ML solutions using LLMs, NLP, and Deep Learning models
• Build and optimize Retrieval-Augmented Generation (RAG) pipelines using vector databases
• Develop and deploy CNN–RNN based architectures for multimodal applications (vision, speech, text)
• Integrate AI models into production systems via REST APIs and microservices
• Develop scalable backend services using Python
• Deploy, monitor, and maintain AI solutions on AWS (or other cloud platforms)
• Build and manage end-to-end ML pipelines, including data ingestion, training, evaluation, and inference
• Optimize model performance for latency, scalability, and cost efficiency
• Collaborate with cross-functional teams to translate business requirements into AI solutions
• Implement CI/CD pipelines for model deployment and continuous integration
• Ensure best practices in model governance, security, and compliance

Requirements

• 3+ years of programming experience in Python
• Strong hands-on experience with LLMs (Eg: Claude)
• Experience building RAG pipelines and vector search systems
• Solid understanding of Machine Learning & Deep Learning concepts
• Experience with CNN, RNN, or Hybrid architectures
• Experience in Natural Language Processing (NLP)
• Experience with REST APIs and Microservices architecture
• Hands-on experience with AWS services
• Experience with Docker and CI/CD tools, GitHub, Jenkins
• Experience with frameworks like TensorFlow or PyTorch
• Experience with LangChain, LangGraph, or AI agent frameworks
• Experience with multimodal AI systems
• Experience in data pipelines and distributed systems
• This role requires weekend on call support

Responsibilities

• Design and develop AI/ML solutions using LLMs, NLP, and Deep Learning models
• Build and optimize Retrieval-Augmented Generation (RAG) pipelines using vector databases
• Develop and deploy CNN–RNN based architectures for multimodal applications (vision, speech, text)
• Integrate AI models into production systems via REST APIs and microservices
• Develop scalable backend services using Python
• Deploy, monitor, and maintain AI solutions on AWS (or other cloud platforms)
• Build and manage end-to-end ML pipelines, including data ingestion, training, evaluation, and inference
• Optimize model performance for latency, scalability, and cost efficiency
• Collaborate with cross-functional teams to translate business requirements into AI solutions
• Implement CI/CD pipelines for model deployment and continuous integration
• Ensure best practices in model governance, security, and compliance

Requirements

• Strong 3 years of programming experience in Python
• Strong hands-on experience with LLMs (Eg: Claude)
• Experience building RAG pipelines and vector search systems
• Solid understanding of Machine Learning & Deep Learning concepts
• Experience with CNN, RNN, or Hybrid architectures
• Experience in Natural Language Processing (NLP)
• Experience with REST APIs and Microservices architecture
• Hands-on experience with AWS services
• Experience with Docker and CI/CD tools, GitHub, Jenkins
• Experience with frameworks like TensorFlow or PyTorch
• Experience with LangChain, LangGraph, or AI agent frameworks
• Experience with multimodal AI systems
• Experience in data pipelines and distributed systems

Responsibilities

• Design and develop AI/ML solutions using LLMs, NLP, and Deep Learning models
• Build and optimize Retrieval-Augmented Generation (RAG) pipelines using vector databases
• Develop and deploy CNN–RNN based architectures for multimodal applications (vision, speech, text)
• Integrate AI models into production systems via REST APIs and microservices
• Develop scalable backend services using Python
• Deploy, monitor, and maintain AI solutions on AWS (or other cloud platforms)
• Build and manage end-to-end ML pipelines, including data ingestion, training, evaluation, and inference
• Optimize model performance for latency, scalability, and cost efficiency
• Collaborate with cross-functional teams to translate business requirements into AI solutions
• Implement CI/CD pipelines for model deployment and continuous integration
• Ensure best practices in model governance, security, and compliance

Requirements

• Strong 3 years of programming experience in Python
• Strong hands-on experience with LLMs (Eg: Claude)
• Experience building RAG pipelines and vector search systems
• Solid understanding of Machine Learning & Deep Learning concepts
• Experience with CNN, RNN, or Hybrid architectures
• Experience in Natural Language Processing (NLP)
• Experience with REST APIs and Microservices architecture
• Hands-on experience with AWS services
• Experience with Docker and CI/CD tools, GitHub, Jenkins
• Experience with frameworks like TensorFlow or PyTorch
• Experience with LangChain, LangGraph, or AI agent frameworks
• Experience with multimodal AI systems
• Experience in data pipelines and distributed systems

Responsibilities

• Design and develop AI/ML solutions using LLMs, NLP, and Deep Learning models
• Build and optimize Retrieval-Augmented Generation (RAG) pipelines using vector databases
• Develop and deploy CNN–RNN based architectures for multimodal applications (vision, speech, text)
• Integrate AI models into production systems via REST APIs and microservices
• Develop scalable backend services using Python
• Deploy, monitor, and maintain AI solutions on AWS (or other cloud platforms)
• Build and manage end-to-end ML pipelines, including data ingestion, training, evaluation, and inference
• Optimize model performance for latency, scalability, and cost efficiency
• Collaborate with cross-functional teams to translate business requirements into AI solutions
• Implement CI/CD pipelines for model deployment and continuous integration
• Ensure best practices in model governance, security, and compliance

Requirements

• Strong 3 years of programming experience in Python
• Strong hands-on experience with LLMs (Eg: Claude)
• Experience building RAG pipelines and vector search systems
• Solid understanding of Machine Learning & Deep Learning concepts
• Experience with CNN, RNN, or Hybrid architectures
• Experience in Natural Language Processing (NLP)
• Experience with REST APIs and Microservices architecture
• Hands-on experience with AWS services
• Experience with Docker and CI/CD tools, GitHub, Jenkins
• Experience with frameworks like TensorFlow or PyTorch
• Experience with LangChain, LangGraph, or AI agent frameworks
• Experience with multimodal AI systems
• Experience in data pipelines and distributed systems

Responsibilities

• Architect and deploy LLM-powered and multi-agent AI systems for real-world applications.
• Build context-aware, goal-driven automation solutions integrating NLP, computer vision, and multimodal pipelines.
• Design intelligent workflows leveraging retrieval systems, embeddings, and memory architectures.
• Evaluate and integrate frontier AI models across multiple providers.
• Develop scalable backend services and APIs supporting AI-driven applications.
• Implement asynchronous orchestration and distributed processing pipelines.
• Optimize inference stacks for latency, cost-efficiency, and performance.
• Design data pipelines for continuous model evaluation and retraining.
• Deploy AI applications using containerization and modern CI/CD workflows.
• Implement infrastructure automation and secure cloud architectures.
• Establish monitoring, logging, and drift detection mechanisms for AI services.
• Ensure high availability and reliability of multi-tier applications.
• Prototype and validate AI concepts through structured experimentation.
• Conduct performance benchmarking across latency, accuracy, and system stability metrics.
• Translate research findings into production-ready systems.
• Maintain documentation for reproducibility and governance.
• Integrate perception systems combining sensor data for real-time decision-making.
• Optimize AI models for edge devices and resource-constrained environments.
• Develop embedded firmware integrations for intelligent hardware systems.
• Lead cross-functional engineering initiatives involving AI, frontend, and cloud teams.
• Mentor junior engineers and foster rapid experimentation cycles.
• Communicate technical trade-offs and system impact clearly to stakeholders.
• Contribute to product strategy through measurable AI-driven insights.

Requirements

• 3+ years of experience in AI Engineering with supporting and delivering.
• Strong programming expertise in Python and C/C++
• Embedded C, FreeRTOS, REST APIs, IoT Systems, Linux
• Experience building LLM-based systems and multi-agent architectures
• Hands-on experience of cloud platforms (AWS, Azure, or GCP)
• Experience with Docker and CI/CD pipelines
• Strong experience in AI and Machine Learning
• Experience in CRM & Project Delivery
• Strong hands-on experience in L2 support, incident resolution, root-cause analysis, monitoring design, and performance optimization across distributed systems.
• Understanding of distributed systems and REST-based integrations
• Experience ML frameworks such as TensorFlow or PyTorch
• Strong experience in debugging, monitoring, and incident resolution capabilities
• Good knowledge in professional skills such as Incident Analysis & Root Cause Identification, Technical Leadership, Clear Communication, Cross-Team Collaboration