Overview:
One of our clients based in California, USA is building a new team and looking for 7 highly skilled and motivated AI Engineers globally to join their dynamic team. As an AI Engineer, you will be pivotal in designing, developing, and deploying state-of-the-art AI solutions that enhance the capabilities of our products and services, driving efficiency and innovation.
Key Responsibilities:
- Design and implement advanced machine learning algorithms to solve complex problems.
- Analyze large datasets to extract valuable insights and improve model performance.
- Train machine learning models and evaluate their performance using various metrics and methodologies.
- Integrate AI solutions into existing systems to enhance functionality and performance.
- Stay updated with the latest trends in AI and machine learning, applying this knowledge to drive innovation within the team.
- Work closely with cross-functional teams, including data scientists, software engineers, and product managers, to deliver high-quality AI solutions.
- Deploy AI models into production environments, ensuring their ongoing performance and reliability.
- Create comprehensive documentation for AI models, algorithms, and systems to facilitate knowledge sharing and maintenance.
Qualifications:
- Bachelors or Masters degree in Computer Science, Engineering, or a related field.
- Proficiency in programming languages such as Python, R, or Java, and strong understanding of machine learning frameworks like TensorFlow, PyTorch, and scikit-learn.
- Demonstrated experience in developing and deploying AI models in a professional setting.
- Strong analytical and problem-solving skills with experience in working with large datasets.
- Excellent verbal and written communication skills to explain complex AI concepts to non-technical stakeholders.
- Ability to work collaboratively in a team environment and contribute to project success.
Preferred Qualifications:
- Ph.D. in AI, Machine Learning, Data Science, or a related field.
- Experience in applying AI techniques in industries such as healthcare, finance, or e-commerce.
- Familiarity with big data platforms like Hadoop, Spark, and AWS.
- Published research in reputable AI or machine learning conferences or journals.