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AI Developer (Remote, Global)

Copenhagen, Capital Region
Posted 1 week ago
Software Development

About the role

Job summary

Seeking an AI Developer to lead AI initiatives from concept to production, collaborating with engineering, product design, and QA teams to deliver customer-facing AI solutions.

Qualifications

  • Over 3 years of experience in developing and deploying production-level AI/ML models.
  • Hands-on experience with MLOps tools such as MLflow, Kubeflow, or Weights & Biases.
  • Strong proficiency in Python and deep learning frameworks like TensorFlow and PyTorch.
  • Experience with LLM orchestration frameworks such as LangChain or LlamaIndex.
  • Proven skills in building and maintaining RESTful APIs using FastAPI or Flask, along with SQL/NoSQL database expertise.
  • Experience in consulting or specialized engineering roles with direct stakeholder interaction.
  • Familiarity with containerization (Docker) and cloud deployment (AWS, GCP, or Azure).
  • Entrepreneurial mindset with the ability to navigate fast-paced environments and solve ambiguous challenges.

Responsibilities

  • Serve as the primary technical partner for customers, translating their operational needs into effective AI solutions.
  • Manage projects from data cleaning and prototyping to deployment, monitoring, and debugging in customer environments.
  • Optimize model performance through techniques like model compression and quantization to meet latency and throughput requirements.
  • Develop advanced prompt engineering strategies and context management for LLM applications.

Skills

  • AI/ML model development and deployment.
  • MLOps tooling and experiment tracking.
  • Python programming and deep learning frameworks.
  • API development and database management.
  • Customer engagement and requirement definition.
  • Cloud deployment and containerization.

Education

  • Relevant degree in Computer Science, Data Science, or a related field is preferred but not mandatory.

Tools

  • MLOps platforms (MLflow, Kubeflow, Weights & Biases).
  • Deep learning frameworks (TensorFlow, PyTorch).
  • API frameworks (FastAPI, Flask).
  • Cloud services (AWS, GCP, Azure).
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