Middle/Senior AI Engineer
vakansiya — 2024

Şirkətlər üçün:

Elan sifarişi:
elan@offer.az
Reklam sifarişi:
reklam@offer.az

Təsvir

  • Model Design & Implementation: Design, develop, and refine state-of-the-art NLP models to tackle specific business or research challenges.
  • Data Strategy: Oversee the collection, preprocessing, and augmentation of diverse text datasets to ensure high-quality inputs for modeling.
  • Optimization & Scaling: Fine-tune NLP solutions for production environments, ensuring scalability and efficiency.
  • Collaboration: Coordinate with cross-functional teams, such as product managers, and software engineers, to seamlessly integrate NLP solutions into products or systems.
  • Research & Development: Stay at the forefront of NLP and ML research, and contribute to internal projects.
  • Mentoring: Offer guidance, training, and mentorship to junior engineers and interns, fostering a culture of continuous learning.

Tələblər

Educational Background:

  • Holding a Bachelor’s/Master’s degree, preferably in Computer Science, Data Science, Linguistics, or a closely related field. A PhD in a relevant domain can be a distinguishing asset.

Technical Skills:

  • Python: Advanced proficiency, with a strong grasp on algorithm design, data manipulation, and optimization techniques.
  • Machine Learning: Solid understanding of a wide range of ML algorithms, with a focus on those frequently used in NLP tasks.
  • Frameworks: In-depth experience with TensorFlow, Keras, PyTorch, or similar, with an emphasis on designing and implementing custom architectures and solutions.
  • Mathematics: Deep knowledge in areas like linear algebra, calculus, and statistics, ensuring a robust understanding of underlying ML principles.
  • Data Tools: Expertise in handling, processing, and analyzing large datasets using tools like Pandas, Numpy, and SQL databases.
  • NLP: Comprehensive understanding of modern NLP tasks, tools, and techniques. Expertise in using and adapting libraries like NLTK, SpaCy, and HuggingFace.

Soft Skills:

  • Communication: Ability to explain intricate NLP and ML concepts to both technical and non-technical stakeholders.
  • Teamwork: Capable of leading collaborative projects and guiding junior team members and interns.
  • Innovation: A strong drive to identify and pursue new techniques or solutions in the NLP domain.

Link https://qlor.me/lw50zmc90k

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