Artificial Intelligence Engineer

Key Responsibilities:

• AI Solution Design and Development:
• Designing, developing, and deploying complex AI/ML models and systems.
• Selecting and implementing appropriate algorithms and frameworks.
• Building scalable and efficient AI pipelines.
• Model Training and Evaluation:
• Training and fine-tuning machine learning models using large datasets.
• Evaluating model performance and optimizing for accuracy and efficiency.
• Implementing model monitoring and retraining strategies.
• Software Development and Integration:
• Integrating AI models into existing software systems.
• Developing APIs and other interfaces for AI services.
• Writing clean, efficient, and well-documented code.
• Research and Innovation:
• Staying up-to-date with the latest AI research and trends.
• Exploring and evaluating new AI technologies and techniques.
• Contributing to research and development efforts.
• Leadership and Collaboration:
• Leading and mentoring junior AI engineers.
• Collaborating with cross-functional teams, including data scientists, software engineers, and product managers.
• Communicating complex technical concepts to non-technical stakeholders.
• Solution Architecture:
• Designing the architecture of AI powered solutions, insuring scalability, and reliability.

Requirements

Required Skills and Qualifications:

• Education:
• A bachelor's or master's degree in computer science, artificial intelligence, machine learning, or a related field.
• Experience:
• Significant experience in AI/ML development, typically 5+ years.
• Proven track record of deploying AI solutions in production environments.
• Experience with deep learning frameworks (TensorFlow, PyTorch, etc.).
• Experience with cloud platforms (AWS, Azure, GCP).
• Technical Skills:
• Proficiency in programming languages such as Python, Java, or C++.
• Strong understanding of machine learning algorithms and deep learning techniques.
• Experience with natural language processing (NLP), computer vision, or other AI subfields.
• Knowledge of data engineering principles and practices.
• Familiarity with containerization and orchestration tools (Docker, Kubernetes).
• Soft Skills:
• Strong problem-solving and analytical skills.
• Excellent communication and collaboration skills.
• Ability to work independently and as part of a team.
• Leadership qualities.

Job Type: Full-time