We are seeking a motivated AI Engineer to join our dynamic team. This role is ideal for individuals with 1-2 years of practical experience in artificial intelligence and machine learning. As a Junior AI Engineer, you will collaborate closely with senior team members to design, develop, and implement AI solutions that solve complex business challenges. This is a hands-on role that requires a solid understanding of machine learning algorithms, data analysis, and programming skills.
Responsibilities:
- Assist in developing AI models and algorithms based on business requirements
- Perform data analysis and prepare data sets for model training and validation
- Implement machine learning pipelines
- Collaborate with cross-functional teams to integrate AI capabilities into existing systems
- Conduct experiments to optimize model performance and scalability
- Stay updated with the latest AI research and technologies
Requirements
- Bachelor's degree in Computer Science, Engineering, or a related field
- 1-2 years of experience in AI, machine learning, or data science roles
- Proficiency in Python, TensorFlow, PyTorch, or similar tools and frameworks
- Strong analytical and problem-solving skills
- Good understanding of data structures, algorithms, and statistical techniques
- Familiarity with prompt engineering techniques and using LLM APIs (OpenAI, Claude, etc.)
- Basic understanding of RAG (Retrieval-Augmented Generation) pipelines and vector databases (e.g., FAISS, Pinecone)
- Exposure to LLM-based agent frameworks or orchestration tools is a plus
- Solid understanding of MLOps principles, including model versioning, deployment, monitoring, and CI/CD pipelines for machine learning workflows
- Excellent communication and teamwork skills
Preferred Qualifications:
- Experience with cloud platforms (e.g., AWS, Azure, Google Cloud)
- Knowledge of natural language processing (NLP) or computer vision (CV) technologies
- Familiarity with tools like LangChain, LlamaIndex, or Hugging Face Transformers
- Understanding of embeddings and chunking strategies for document-based AI systems
- Familiarity with DevOps practices and tools
