Artificial Intelligence and Machine Learning Engineer

Overview: 

As a Mid-Level Artificial Intelligence and Machine Learning Engineer at Khonology, you will be part of a dynamic team responsible for developing cutting-edge AI and ML solutions. You will collaborate with cross-functional teams to design, implement, and deploy AI models and algorithms to solve challenging business problems. This role offers an opportunity to work on diverse projects and leverage the latest technologies in AI and machine learning.

Responsibilities:

Design and implement machine learning models and algorithms to address specific business challenges.

Develop scalable and efficient methods for large-scale data analysis and model training.

Collaborate with software engineers to integrate AI models into production systems.

Evaluate and benchmark the performance of AI models.

Research and stay up-to-date with the latest advancements in AI and machine learning technologies.

Work closely with stakeholders to understand business requirements and translate them into technical solutions.

Mentor junior members of the team and provide technical guidance.

Requirements:

Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field.

X+ years of experience in developing AI and machine learning solutions in a professional environment.

Proficiency in programming languages such as Python, .Net or Java, or C++.

Strong understanding of machine learning techniques and algorithms, such as neural networks, SVM, decision trees, etc.

Hands-on experience with machine learning frameworks/libraries such as TensorFlow, PyTorch, scikit-learn, etc.

Experience with data preprocessing, feature engineering, and model tuning.

Familiarity with cloud platforms (AWS, Azure, Google Cloud) and their AI/ML services.

Excellent problem-solving skills and ability to work independently as well as part of a team.

Strong communication skills and ability to explain complex technical concepts to non-technical stakeholders.

Preferred Qualifications:

• PhD in Computer Science, Engineering, Mathematics, or a related field.
• Experience with big data technologies such as Hadoop, Spark, etc.
• Knowledge of deep learning techniques and frameworks.
• Previous experience in deploying AI/ML models in production environments.
• Contributions to open-source AI/ML projects or research publications.