Job Title: AI Engineer

Location: Mohali (Onsite)
Shift: UK Shift (12 PM to 10 PM)
Experience: 1 to 2 years

Qualifications:

• Bachelor's degree in Computer Science, Business, or a related field.
• Specialization or certification in AI/ML is a plus.

Job Role & Responsibilities:

• Develop and optimize predictive models for AI and ML-based features, focusing on enhancing accuracy and latency.
• Write clean, efficient, reusable, testable, and scalable code with a focus on best coding practices.
• Analyze business requirements, translate them into software components, and implement feature modifications.
• Design and implement high-availability, low-latency applications with data protection and security features.
• Profile applications to ensure optimal performance and identify potential bottlenecks.
• Continuously work on optimizing NLP-based models, improving both their accuracy and latency for real-world applications.
• Write unit test cases to ensure code quality and reliability, using appropriate testing frameworks.
• Continuously optimize and refactor code for improved performance, scalability, and maintainability.

Skills & Expertise:

• Strong expertise in building solutions using AI/ML/DL open-source libraries.
• Advanced Python programming skills.
• Strong problem-solving and analytical abilities.
• Ability to write optimized, well-documented code following best coding practices.
• Proficient in optimizing models for both accuracy and latency, particularly in NLP and machine learning applications.
• Proficient in optimizing NLP-based models, including techniques for faster inference and reduced computational cost.
• Familiarity with Generative AI, Large Language Models (LLM), Embeddings, Vectors, RAG (Retrieval-Augmented Generation), and Prompting.

Tools & Technologies:

• AI/ML Libraries: TensorFlow, PyTorch, Flair, BERT, DeBERTa, and other latest libraries for text analytics.
• Frameworks & Platforms: Streamlit, FastAPI.
• Specialized Tools: Ollama, Vector Databases.
• Profiling & Testing: Familiarity with tools for profiling applications (e.g., cProfile, Py-Spy) and writing unit tests (e.g., PyTest, UnitTest).
• Optimization Techniques: Techniques such as model quantization, pruning, distillation, and hardware acceleration.

Technical Expertise:

• Minimum of 1 year of hands-on experience in AI/ML/DL projects, focusing on Natural Language Processing (NLP), Named Entity Recognition (NER), and Text Analytics.
• Strong understanding and practical experience with deep learning techniques, including recommendation engines and advanced AI solutions.
• Proven experience in optimizing NLP models for accuracy and latency in production environments.
• Experience with Retrieval-Augmented Generation (RAG) application development and generative AI.
• Familiarity with Agent Prompting and its applications.
• Experience in AI applications within the HR domain is highly preferred.
• Knowledge of Reinforcement Learning is a plus.
• Certifications or specialization in Artificial Intelligence is highly desirable.