AI ENGINEER

Job Description

We are seeking a skilled and motivated AI Engineer to join our innovative team at Talent Fusion. This position plays a critical role in designing, developing, and deploying AI-driven solutions to enhance our recruitment platform. If you have a strong foundation in Natural Language Processing (NLP), Natural Language Understanding (NLU), and Named Entity Recognition (NER), along with at least 2 years of experience in the AI field, we would love to hear from you.

Responsibilities:

· Design, develop, and implement AI models focused on NLP, NLU, and NER to process, analyze, and extract meaningful insights from recruitment-related data.

· Collaborate with cross-functional teams (data scientists, software engineers, and product managers) to integrate AI solutions into our recruitment platform.

· Build and optimize machine learning pipelines for tasks such as resume parsing, job-candidate matching, recommendation engines, and skills extraction.

· Continuously fine-tune models to improve performance, scalability, and accuracy in real-world scenarios.

· Explore and apply state-of-the-art techniques in deep learning and transformer-based architectures (e.g., BERT, GPT, etc.) to enhance NLP capabilities.

· Develop APIs to expose AI functionalities for seamless integration with microservices architecture.

· Monitor, debug, and improve deployed AI systems to ensure they meet performance and reliability standards.

· Stay updated on industry trends, emerging technologies, and advancements in AI to recommend and implement innovative solutions.

Job Requirement

Qualifications:

· Education: Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.

· Experience: At least 2 years of hands-on experience working with AI technologies, with a strong emphasis on NLP, NLU, or NER projects.

· Skills:

o Proficiency in Python and frameworks such as TensorFlow, PyTorch, or Hugging Face.

o Experience with NLP libraries like spaCy, NLTK, or transformers.

o Knowledge of transformer-based models like BERT, RoBERTa, or GPT.

o Familiarity with large-scale data preprocessing, annotation, and training pipelines.

o Understanding of database systems (SQL/NoSQL) and data structures for efficient model integration.

o Experience deploying AI models in cloud environments (e.g., AWS, Google Cloud, Azure).

o Strong problem-solving skills and the ability to work in an agile environment.

Preferred Qualifications:

· Hands-on experience with NER and custom entity recognition models in real-world applications.

· Knowledge of microservices architecture and integrating AI into distributed systems.

· Experience working with recruitment platforms or similar data-intensive domains.

· Familiarity with Docker, Kubernetes, and CI/CD pipelines for deploying AI solutions.