jobs in Xander Consulting And Advisory Private Limited

Xander Consulting And Advisory Private Limited Hiring! Full Time Artificial Intelligence Engineer - Machine Learning Frameworks in , Earn up to SGD 100,000 - Ricebowl

Artificial Intelligence Engineer - Machine Learning Frameworks

Xander Consulting And Advisory Private Limited

SGD91,667 - SGD100,000 Per Month

Full Time

Remote

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Working Location

  • Remote Singapore

Job Description

Responsibilities

  • You are an AI engineer responsible for designing, developing, and deploying AI models and solutions to address real-world business challenges. Your role will involve hands-on coding, model training, and integration into production systems.

  • **Key Responsibilities:**
  • - Design, build, and fine-tune machine learning, deep learning, and generative AI models for various real-world use cases.
  • - Develop agentic AI systems utilizing frameworks like ADK, LangGraph, or equivalent tools for orchestration and reasoning.
  • - Create solutions leveraging LLMs, RAG pipelines, embeddings, and vector databases.
  • - Design and implement AI systems for text, structured/unstructured data, and conversational use cases.
  • - Apply core NLP techniques such as classification, summarization, entity recognition, and semantic search.
  • - Develop scalable algorithms for search, retrieval, and real-time inference.
  • - Build and integrate AI microservices into enterprise systems using APIs, event-driven architectures, and cloud services.
  • - Deploy and manage AI workloads using Docker, Kubernetes, and managed cloud AI platforms like Azure ML, AWS SageMaker, GCP Vertex AI.
  • - Optimize solutions for performance, cost, latency, and security.
  • - Collect, preprocess, and manage large datasets for fine-tuning and inference.
  • - Continuously monitor and optimize models and prompts for accuracy, scalability, and efficiency.
  • - Collaborate with solution architects and business teams to translate requirements into production-ready AI solutions.
  • - Advocate for Responsible AI practices, including fairness, bias mitigation, and compliance.

  • **Qualifications:**
  • - Proficiency in Python, SQL, and ML frameworks such as TensorFlow and PyTorch.
  • - Strong understanding of generative AI concepts including transformers, embeddings, and fine-tuning.
  • - Experience with Agentic AI frameworks like ADK, LangGraph, AutoGen.
  • - Familiarity with cloud platforms (AWS, Azure, GCP) for AI deployment.
  • - Knowledge of prompt engineering, vector databases like Pinecone and Weaviate, and retrieval-augmented generation (RAG).
  • - Hands-on experience with cloud-native AI deployments on Azure, AWS, and GCP.
  • - Understanding of API-driven design, microservices, and event-driven architectures.

  • **Additional Details:**
  • The company emphasizes the importance of Responsible AI practices, including fairness, bias mitigation, and compliance in their AI solutions development.

  • (Note: Company details have not been provided in the job description) You are an AI engineer responsible for designing, developing, and deploying AI models and solutions to address real-world business challenges. Your role will involve hands-on coding, model training, and integration into production systems.

  • **Key Responsibilities:**
  • - Design, build, and fine-tune machine learning, deep learning, and generative AI models for various real-world use cases.
  • - Develop agentic AI systems utilizing frameworks like ADK, LangGraph, or equivalent tools for orchestration and reasoning.
  • - Create solutions leveraging LLMs, RAG pipelines, embeddings, and vector databases.
  • - Design and implement AI systems for text, structured/unstructured data, and conversational use cases.
  • - Apply core NLP techniques such as classification, summarization, entity recognition, and semantic search.
  • - Develop scalable algorithms for search, retrieval, and real-time inference.
  • - Build and integrate AI microservices into enterprise systems using APIs, event-driven architectures, and cloud services.
  • - Deploy and manage AI workloads using Docker, Kubernetes, and managed cloud AI platforms like Azure ML, AWS SageMaker, GCP Vertex AI.
  • - Optimize solutions for performance, cost, latency, and security.
  • - Collect, preprocess, and manage large datasets for fine-tuning and inference.
  • - Continuously monitor and optimize models and prompts for accuracy, scalability, and efficiency.
  • - Collaborate with solution architects and business teams to translate requirements into production-ready AI solutions.
  • - Advocate for Responsible AI practices, including fairness, bias mitigation, and compliance.

  • **Qualifications:**
  • - Proficiency in Python, SQL, and ML frameworks such as TensorFlow and PyTorch.
  • - Strong understanding of generative AI concepts including transformers, embeddings, and fine-tuning.
  • - Experience with Agentic AI frameworks like ADK, LangGraph, AutoGen.
  • - Familiarity with cloud platforms (AWS, Azure, GCP) for AI deployment.
  • - Knowledge of prompt engineering, vector databases like Pinecone and Weaviate, and retrieval-augmented generation (RAG).
  • - Hands-on experience with cloud-native AI deployments on Azure, AWS, and GCP.
  • - Understanding of API-driven design, microservices, and event-driven architectures.

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