Artificial Intelligence Engineer

Job Description

We are looking for an experienced Artificial Intelligence (AI) Engineer to design, develop, and implement AI-driven solutions that meet our business and operational needs. The ideal candidate will be skilled in machine learning, deep learning, and data analysis, with a proven ability to build and deploy AI models to solve complex problems. This role requires close collaboration with cross-functional teams, including data scientists, software engineers, and product managers, to create impactful AI applications.

Key Responsibilities:

• Design, develop, and deploy AI models, including machine learning (ML) and deep learning (DL) models, for applications across various domains.
• Collaborate with data scientists and data engineers to gather and preprocess data for training and validation.
• Develop custom machine learning algorithms tailored to specific business needs, utilizing supervised, unsupervised, and reinforcement learning techniques.
• Fine-tune models to optimize accuracy, performance, and scalability for real-world applications.
• Implement model evaluation metrics and monitor model performance over time, retraining as necessary.
• Integrate AI models into production environments, collaborating with software development teams for seamless deployment.
• Build and maintain pipelines for continuous model training and improvement, incorporating feedback from production data.
• Conduct regular research on emerging AI tools, frameworks, and best practices to ensure solutions remain at the cutting edge.
• Document all processes, including model development, deployment, and testing, to ensure reproducibility and scalability.
• Ensure compliance with data privacy and ethical AI guidelines throughout the development lifecycle.

Requirements:

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
• Strong proficiency in programming languages, particularly Python, and experience with AI/ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
• Solid understanding of machine learning and deep learning algorithms, including neural networks, clustering, decision trees, and natural language processing (NLP).
• Experience with data preprocessing techniques, feature engineering, and model evaluation.
• Proficiency with cloud platforms (e.g., AWS, Azure, Google Cloud) and familiarity with MLOps tools for model deployment and monitoring.
• Knowledge of data storage and processing technologies (e.g., SQL, NoSQL, Hadoop, Spark).
• Strong analytical skills with an ability to troubleshoot complex model issues and optimize performance.
• Excellent communication skills to explain complex AI concepts to non-technical stakeholders.

Preferred Qualifications:

• Experience with computer vision, NLP, or reinforcement learning.
• Knowledge of data privacy laws and ethical AI practices.
• Certifications in AI, machine learning, or cloud platforms (e.g., AWS Certified Machine Learning, Google Cloud AI Engineer).
• Familiarity with big data processing frameworks and distributed computing.