Job Description:

We are looking for a talented AI/ML Engineer to join our innovative team. In this role, you will develop and deploy machine learning models that solve complex problems and drive data-driven decision-making. You will work closely with data scientists, software engineers, and business stakeholders to create scalable and efficient AI solutions that impact real-world applications.

Responsibilities:

As an AI/ML Engineer, you will design, build, and optimize machine learning algorithms and systems. Your work will include data preprocessing, model training, evaluation, and deployment. Collaboration and continuous learning are key, as you help improve the performance and reliability of AI-powered products.

• Develop and implement machine learning models and algorithms

• Work with large datasets to extract meaningful insights

• Collaborate with cross-functional teams to integrate AI solutions into production

• Monitor model performance and fine-tune for accuracy and efficiency

• Stay updated with the latest AI/ML research and tools
  
  

Qualifications:

The ideal candidate will have a strong background in computer science, mathematics, or a related field, with hands-on experience in machine learning. A solid understanding of algorithms, data structures, and statistics is essential. Familiarity with AI frameworks and programming languages is also important.

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field

• Experience with machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn

• Proficiency in programming languages like Python or R

• Strong foundation in mathematics, statistics, and data analysis

• Ability to work with large datasets and cloud platforms
  
  

Nice to Have:

Additional skills and knowledge that will help you excel in this role include experience with advanced AI techniques, deployment tools, and collaborative workflows. Passion for innovation and continuous learning is highly valued.

• Experience with deep learning and neural networks

• Familiarity with cloud services like AWS, Azure, or GCP

• Knowledge of containerization and orchestration tools such as Docker and Kubernetes

• Understanding of natural language processing (NLP) or computer vision

• Contributions to open-source AI/ML projects or research publications