AI Engineer / Consultant / Developer

Job Description:

We are seeking a skilled and experienced AI Engineer / Consultant / Developer and Machine Learning Engineers/Developers to join our team. The ideal candidates will have a strong background in artificial intelligence, machine learning, and software development, with expertise in Python and CI/CD processes.

Key Responsibilities:
• Design, develop, and implement AI and machine learning models and solutions.
• Collaborate with cross-functional teams to define, design, and ship new AI-driven features.
• Optimize and fine-tune machine learning algorithms for high performance and scalability.
• Implement Continuous Integration/Continuous Deployment (CI/CD) pipelines to automate the testing and deployment of ML models.
• Analyze data and provide insights to improve AI/ML models and business processes.
• Monitor and maintain AI/ML models in production to ensure reliability and performance.
• Stay updated with the latest AI/ML trends and technologies and apply them to ongoing projects.
• Provide technical guidance and support to other team members on AI/ML-related projects.

Key Requirements:
• Experience: Minimum 3+ years of hands-on experience in AI, Machine Learning, or Data Science.
• Technical Skills:
• Proficient in Python and relevant AI/ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Strong understanding of algorithms, data structures, and statistical methods.
• Experience in developing, training, and deploying ML models in production environments.
• Hands-on experience with CI/CD pipelines, tools like Jenkins, GitLab CI, Docker, etc.
• Familiarity with cloud platforms (AWS, GCP, Azure) and deploying AI/ML solutions on the cloud.
• Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• Soft Skills:
• Strong problem-solving skills and ability to work independently.
• Excellent communication and collaboration skills.
• Ability to translate business requirements into technical solutions.

Preferred Qualifications:
• Experience with MLOps practices.
• Knowledge of big data technologies and frameworks (e.g., Hadoop, Spark).
• Experience with RESTful APIs and microservices architecture.