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KRNL Labs

AI Blockchain Engineer

NEW
Bangkok, ThailandFull-timeGlobal

šŸ’° THB 60,000 - 120,000/yr

šŸ“Š MidšŸ  Hybrid
ActivePosted within the last 30 days

Job Description

[AI-summarized by JobStash]

You will design, build, and optimize AI extensions integrated with blockchain infrastructure. You will deploy machine learning and natural language processing models into production and optimize them for performance and scalability. You will debug and resolve complex performance, scalability, and security issues, conduct code reviews, monitor system and model performance, create documentation, and follow Agile and Scrum practices.

Requirements

  • ā—Fluent English reading writing and communication
  • ā—Minimum 3 years of experience in AI development and deployment
  • ā—Hands-on experience with at least one major AI technology related to machine learning or natural language processing
  • ā—Proficient in Python and frameworks such as PyTorch Scikit TensorFlow
  • ā—Proficient in SQL
  • ā—Ability to work in the Bangkok office in Sukhumvit (BTS On Nut) or relocate
  • ā—Excellent communication and collaboration skills and ability to work in an agile team environment
  • ā—Experience with data processing tools such as Java Go Haskell or Apache Spark (preferred)
  • ā—Experience in Web3 or blockchain development (preferred)
  • ā—Familiarity with containerization technologies such as Docker and CI/CD pipelines (preferred)
  • ā—Professional certifications from cloud providers such as GCP AWS or Azure (preferred)
  • ā—Bachelor's or Master's degree in Computer Science Data Engineering or related field or equivalent experience (preferred)
  • ā—Demonstrated ability to design and implement optimized performant and scalable code (preferred)

Responsibilities

  • ā—Debug and resolve complex issues related to performance scalability and security in blockchain and AI integration
  • ā—Conduct code reviews and optimize performance in blockchain environments and AI models
  • ā—Deploy models and algorithms into production and optimize them for performance and scalability
  • ā—Monitor and optimize AI performance and resolve bottlenecks and inefficiencies
  • ā—Create detailed documentation and provide regular status updates
  • ā—Research and document AI-related projects and development tools
  • ā—Employ Agile and Scrum methodologies and follow software lifecycle best practices

Tech Stack

Apache SparkTensorFlowscikit-learnPyTorchmachine learningDockerdata engineeringPython
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