AI Engineer

Your tasks

• Design, develop, train, evaluate, and optimize Machine Learning and AI models for business use cases.
• Prepare, transform, and analyze structured and unstructured data for model development and AI applications.

• Develop AI solutions using Machine Learning, Deep Learning, Predictive Analytics, NLP, Generative AI, and other relevant technologies.
• Build Generative AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, and Agentic Workflows.

• Design and optimize retrieval pipelines, including embeddings, vector databases, vector search, reranking, and context optimization.
• Integrate AI solutions with internal systems, databases, APIs, microservices, and third-party services.

• Deploy and operate AI/ML solutions in cloud or enterprise environments and support production implementation.
• Apply MLOps and LLMOps practices, including model deployment, monitoring, testing, retraining, versioning, and lifecycle management.

• Translate business requirements and operational challenges into practical and scalable AI/ML solution designs.
• Take ownership of assigned AI initiatives from problem framing and solution design through development, deployment, monitoring, and continuous improvement.

• Collaborate with business stakeholders, Data Engineering, Infrastructure, and other cross-functional teams to design, integrate, and deliver AI solutions.

Requirements

We are looking for a hands-on AI Engineer with strong Machine Learning and Generative AI capabilities who can deliver reliable, scalable, and production-ready AI solutions. The ideal candidate should be able to work across the full AI lifecycle, take ownership of assigned initiatives, collaborate with cross-functional teams, and drive solutions from problem definition through production implementation.

1. Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Engineering, Statistics, Mathematics, or a related field.
2. 4+ years of relevant experience in Machine Learning, Data Science, or related roles, including at least 2 years of hands-on experience in AI Engineering, Generative AI, or Large Language Model (LLM) applications.
3. Strong programming skills in Python and SQL.
4. Hands-on experience developing Machine Learning solutions, including data preparation, feature engineering, model selection, training, validation, evaluation, and deployment.
5. Practical experience with Machine Learning and Deep Learning frameworks and architectures such as Scikit-learn, PyTorch, TensorFlow, Transformer architectures, or similar technologies.
6. Strong understanding of Machine Learning, Statistics, Model Evaluation, and Model Validation.
7. Practical experience with LLMs, RAG, Prompt Engineering, vector databases, and Generative AI applications.
8. Experience deploying AI/ML solutions in cloud environments such as AWS, Azure, or Google Cloud Platform.
9. Ability to collaborate with business and technology teams to design and implement practical AI/ML solutions.