Internship

Job highlights

• Bachelor s or Master s degree in Computer Science,Data Science,or a related field
• Experience with NLP and NLU techniques,including tokenization,sentiment analysis,named entity recognition,and machine translation
• Preferred Qualifications: .
• Proven experience with AI / ML frameworks (e.g.,TensorFlow,PyTorch) and language models

Job Summary: We are seeking a talented and passionate AI/ML Product Engineer to join our team, focusing on the development and deployment of AI/ML-based products. The ideal candidate will work on projects related to Natural Language Understanding (NLU), Natural Language Processing (NLP), automation, and large language models (LLMs). This role will involve fine-tuning existing models, building new features, and exploring innovative product ideas that enhance and expand our product suite.

Key Responsibilities:

• Design, build, and maintain AI/ML models, especially focusing on NLP, NLU, and automation use cases.

• Fine-tune and optimize pre-trained models to improve performance in specific applications, leveraging advanced LLMs and similar architectures.

• Collaborate with cross-functional teams to ideate, experiment, and implement new product ideas that utilize AI/ML technologies effectively.

• Research and explore new advancements in AI/ML, recommending tools and techniques that can drive innovative solutions for real-world problems.

• Develop and execute proof-of-concept projects to demonstrate the feasibility and value of new AI/ML ideas.

• Ensure scalability and efficiency of models by conducting performance tests, evaluations, and iterations based on feedback.

• Write and maintain robust code, following best practices for software development and model deployment.

Preferred Qualifications:

• Bachelor s or Master s degree in Computer Science, Data Science, or a related field.

• Proven experience with AI/ML frameworks (e.g., TensorFlow, PyTorch) and language models.

• Strong programming skills in Python, along with libraries such as NumPy, Pandas, and scikit-learn.

• Experience with NLP and NLU techniques, including tokenization, sentiment analysis, named entity recognition, and machine translation.

• Familiarity with LLMs, prompt engineering, fine-tuning, and related techniques.

• Solid understanding of data preprocessing, feature engineering, and model evaluation methods.

• Ability to collaborate effectively with product teams and translate business requirements into technical implementations.

Requirements and Skills :

• Strong analytical and problem-solving skills.

• Ability to work independently and as part of a collaborative team.

• Adaptable and eager to learn new tools, techniques, and technologies.

Job Category: Development