AI ENGINEER

We are seeking a skilled and innovative AI Developer to join our team and contribute to cutting-edge projects in artificial intelligence. The ideal candidate will have at least 2 years of proven experience in AI projects and a deep understanding of Large Language Models (LLMs), Robotic Process Automation (RPA), and Generative AI. This role involves designing, implementing, and optimizing machine learning and deep learning solutions to solve complex business challenges.

Key Responsibilities

1. AI Development and Deployment:

   • Design, develop, and deploy AI models using state-of-the-art techniques in machine learning and deep learning.

   • Build scalable solutions leveraging LLMs and Generative AI for real-world applications.

2. RPA Integration:

   • Develop AI-powered RPA workflows to automate repetitive tasks and enhance operational efficiency.

   • Integrate machine learning models into RPA pipelines for smarter decision-making.

3. Research and Prototyping:

   • Explore and experiment with emerging AI technologies, focusing on LLMs and Generative AI models like GPT, DALL·E, or similar frameworks.

   • Create prototypes to validate new AI concepts and solutions.

4. Data Management:

   • Preprocess and analyze large datasets to train and fine-tune AI models.

   • Implement data augmentation and synthetic data generation techniques when necessary.

5. Collaboration:

   • Work closely with cross-functional teams, including product managers, data engineers, and software developers, to align AI solutions with business objectives.

   • Provide technical guidance and mentorship to junior developers when required.

6. Performance Optimization:

   • Monitor and optimize the performance of AI systems in production environments to ensure efficiency and reliability.

   • Address scalability challenges in machine learning pipelines.

Qualifications and Skills

Required Skills

• Strong knowledge of Large Language Models (LLMs) and their applications.

• Experience with Generative AI frameworks and tools (e.g., GPT, Stable Diffusion, DALL·E).

• Proficiency in Robotic Process Automation (RPA) tools and their integration with AI solutions.

• Understanding of machine learning or deep learning techniques, algorithms, and frameworks.

• Hands-on experience with libraries and frameworks such as TensorFlow, PyTorch, Keras, or Hugging Face Transformers.

• Proficiency in programming languages such as Python (preferred), R, or JavaScript.