AI 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.

Required Skills and Qualifications:

• Education:
• A bachelors or masters 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.