Artificial Intelligence Engineer

We are seeking a highly skilled AI Engineer to design, develop, and deploy machine learning and artificial intelligence models. You will work closely with data scientists, software engineers, and product teams to build intelligent solutions that enhance our products and services. This role requires a combination of programming expertise, deep learning knowledge, and an understanding of cloud-based AI technologies.

Complete your profile to be reviewed by our Matching team! If you're the right fit, we'll reach out with opportunities. Due to the high volume of applicants, we may not always provide feedback, but your profile will be considered for future openings.

Responsibilities:

• Design and implement machine learning (ML) models and AI algorithms.
• Preprocess and analyze large datasets to train and fine-tune AI models.
• Optimize and deploy models into production environments (on-premise or cloud).
• Collaborate with data scientists and engineers to integrate AI solutions into applications.
• Improve model performance through hyperparameter tuning and optimization.
• Develop APIs and services for AI-powered applications.
• Stay updated with the latest advancements in AI and ML technologies.
• Ensure ethical AI practices and compliance with relevant regulations.

Requirements:

• Proficiency in programming languages such as Python, Java, or C++.
• Experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn, etc.).
• Knowledge of deep learning architectures (CNNs, RNNs, Transformers).
• Familiarity with cloud platforms (AWS, Azure, Google Cloud Platform) for AI deployment.
• Experience in data engineering (ETL, data preprocessing, SQL/NoSQL databases).
• Experience with MLOps and CI/CD pipelines for AI models is desirable.
• Strong problem-solving skills and ability to work in agile development teams.
• English - Advanced level

Nice to Have:

• Hands-on experience with LLMs (Large Language Models) and Generative AI.
• Understanding of NLP, Computer Vision, or Reinforcement Learning is a plus.
• Knowledge of vector databases, embeddings, and retrieval-augmented generation (RAG).
• Experience in real-time AI applications and model inferencing optimization.
• Contributions to open-source AI projects or published research papers.