Generative AI Engineer

Mactores is a trusted leader among businesses in providing modern data platform solutions. Since 2008, Mactores have been enabling businesses to accelerate their value through automation by providing End-to-End Data Solutions that are automated, agile, and secure. We collaborate with customers to strategize, navigate, and accelerate an ideal path forward with a digital transformation via assessments, migration, or modernization.

We are seeking a highly skilled and innovative Generative AI Engineer to join our team. In this role, you will develop and deploy cutting-edge generative AI models to solve real-world problems. You will work on building models that generate content, understand complex data, and collaborate closely with cross-functional teams to implement AI-powered solutions.

What you will do?

Design, develop, and train generative models (such as GANs, VAEs, Diffusion models, Transformer-based models like GPT, etc.) for various use cases, including image, text, and speech generation.

Fine-tune large pre-trained models to specific domains and tasks.

Research and implement state-of-the-art techniques for improving model accuracy, efficiency, and scalability.

Work with large-scale datasets, including data cleaning, annotation, augmentation, and preparation for model training.

Collaborate with Data Engineering teams to ensure proper data pipelines and infrastructure are in place.

Develop and deploy generative AI models into production systems.

Optimize models for inference speed, accuracy, and efficiency in cloud or edge environments.

Ensure models are scalable, reliable, and maintainable.

Stay up-to-date with the latest advancements in generative AI and related fields.

Participate in AI research projects, publish papers, or contribute to open-source communities.

Innovate and prototype new applications for generative AI.

Work closely with software engineers, product managers, and domain experts to integrate AI solutions into existing systems and workflows.

Translate technical concepts to non-technical stakeholders.

What are we looking for?

Bachelor’s or Master’s degree in Computer Science, AI, Machine Learning, or a related field (PhD preferred).

3+ years of experience working with deep learning frameworks (e.g., TensorFlow, PyTorch).

Strong background in machine learning algorithms, specifically generative models like GANs, VAEs, transformers, etc.

Proficiency in Python and experience with other programming languages like Java or C++ is a plus.

Experience with cloud platforms (AWS, GCP, or Azure) and deploying AI models in production.

Knowledge about LLMs like Claude, Mistral, etc., and their variations, especially text-based likes GPT, BERT, T5, etc.

Strong understanding of hyperparameter tuning methods and experience applying transfer learning to optimize model performance and efficiency.

Solid understanding of deep learning techniques, neural networks, and generative adversarial models.

Strong analytical, problem-solving, and debugging skills.

Preferred Qualifications

Experience with NLP, computer vision, and multimodal models.

Experience with Sagemaker and Amazon Bedrock.

Familiarity with reinforcement learning techniques in generative modeling.

Experience working with tools like Hugging Face, OpenAI API, and similar AI/ML libraries.

Knowledge of MLOps tools and practices for continuous deployment and monitoring of AI models.

Understanding of autoregressive models is a plus.

A strong publication record in top-tier AI/ML conferences or journals is an advantage.