Roles Responsibilities
- Design and develop advanced AI models and algorithms, including machine learning, deep learning, and natural language processing.
- Lead the end-to-end development process of AI solutions, from data collection and preprocessing to model training, evaluation, and deployment.
- Collaborate with data scientists, software engineers, and product managers to identify business needs and translate them into technical requirements.
- Mentor and guide junior engineers, providing technical leadership and fostering a culture of continuous learning and improvement.
- Conduct research to stay updated on the latest AI trends, technologies, and best practices, and apply this knowledge to enhance our AI capabilities.
- Optimize and fine-tune existing AI models for performance, scalability, and accuracy.
- Develop and maintain documentation for AI models, processes, and best practices.
- Ensure compliance with ethical standards and best practices in AI development and deployment.
Technical Skills
- Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field.
- 3+ years of experience in AI/ML engineering or a related field, with a strong portfolio of successful projects.
- Proficiency in programming languages such as Python, Java, or C++ and experience with AI frameworks (e.g., TensorFlow, PyTorch, Keras).
- Strong understanding of machine learning algorithms, statistical modeling, and data analysis techniques.
- Experience with data preprocessing, feature engineering, and model evaluation metrics.
- Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and deployment of AI solutions in production environments.
- Excellent problem-solving skills and the ability to work collaboratively in a team-oriented environment.
- Strong communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.
Qualifications
- Experience in specific domains such as computer vision, natural language processing, or reinforcement learning.
- Knowledge of AI ethics and responsible AI practices.
- Experience with version control systems (e.g., Git) and agile development methodologies.