AI Engineer / Machine Learning Engineer

Key Responsibilities Model Development: Design, develop, and deploy Machine Learning (ML) and Deep Learning models.

Data Engineering: Clean, analyze, and preprocess large datasets to ensure high-quality input for AI models.

NLP & Computer Vision: Implement Natural Language Processing (NLP) tools and Computer Vision algorithms based on project requirements.

Integration: Collaborate with Frontend and Backend developers to integrate AI models into web and mobile applications.

Optimization: Continuously monitor and fine-tune existing models to improve accuracy and performance.

Research: Stay updated with the latest AI trends, frameworks, and research papers to keep the company competitive.

Required Skills & Qualifications Education: Bachelor’s/Master’s degree in Computer Science, Data Science, or a related field.

Programming: Mastery in Python (most critical), R, or Java.

AI Frameworks: Strong experience with TensorFlow, PyTorch, Keras, or Scikit-learn.

Cloud Platforms: Familiarity with AWS (SageMaker), Azure AI, or Google Cloud AI Platform.

Databases: Proficiency in SQL and NoSQL (MongoDB, Pinecone for vector search).

Mathematics: Strong understanding of Linear Algebra, Calculus, and Statistics.

Generative AI (Bonus): Knowledge of LLMs (Large Language Models) like GPT-4, Llama, and prompt engineering is a huge plus.

Soft Skills Problem-Solving: Ability to break down complex business problems into technical AI tasks.

Communication: Ability to explain technical AI concepts to non-technical clients and team members.

Adaptability: Willingness to learn new tools in the rapidly evolving AI landscape.