AI Programmer

PT Infotech Solutions
Daerah Khusus Ibukota Jakarta
IDR 200,000,000 - 300,000,000
Job description

We are looking for a passionate and experienced AI Programmer to join our team. You will be responsible for designing, developing, and implementing Generative AI-based solutions for various company projects. This role requires a deep understanding of machine learning and the latest AI technologies, as well as the ability to apply them in company products and solutions.

Job Description:

  • Research, develop, test, and optimize Generative AI models such as LLM (Large Language Models), GANs, or Diffusion Models according to business needs.
  • Build data pipelines for training, fine-tuning, and deployment of AI models.
  • Collaborate with a team of data scientists, software engineers, and product managers to design scalable and impactful AI solutions.
  • Implement NLP (Natural Language Processing) algorithms for text analysis in media monitoring platforms.
  • Identify areas of improvement in AI products and provide innovative solutions.
  • Document AI model development and ensure a transparent and reproducible process.
  • Stay abreast of the latest developments in AI, including model architectures and open-source approaches.

Requirements:

  • Bachelor’s degree in Computer Science, Engineering, or related field
  • Experience from Entry-level to experience in the Development field
  • Proficiency in Python
  • Experience with deep learning framework such as Pytorch or TensorFlow
  • Ability to implement solutions based on academic papers and technical research
  • Prior research experience in Generative AI and LLMs.
  • Strong analytical thinking and problem-solving skills.
  • Effective communication in cross-functional teams.
  • High motivation and ready to learn the latest technology in the field of AI.

Preferred Qualifications:

  • Experience with Natural Language Processing (NLP) libraries such as Hugging Face Transformers
  • Publications or contributions to open-source project in AI/ML fields
  • Knowledge of MLOps principles for scaling machine learning workflows and automation
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