AI Engineer
RebelDot AI Engineer
You might be our missing piece if you have:
Strong Python skills and hands-on experience with AI/ML frameworks such as PyTorch, TensorFlow, or Keras.
Experience building backend applications and APIs using FastAPI, Flask, or Django.
Solid experience developing AI/ML solutions and applications powered by LLMs.
Research experience and the ability to turn scientific papers and experimental ideas into practical solutions.
Experience working with commercial LLM APIs, embeddings, text generation, and semantic search.
Solid experience integrating external APIs, including OpenAI, Anthropic, or similar AI providers.
Strong data processing skills using tools such as Pandas, NumPy, and SciPy.
Familiarity with relational databases and tools such as SQLAlchemy and Alembic.
Proficiency with Docker and containerized development and deployment.
A solid understanding of clean, maintainable, and PEP 8-compliant Python code.
The ability to communicate complex AI concepts clearly and collaborate effectively with product and engineering teams.
A sense of belonging while reading about our culture.
We would be thrilled if you have:
Experience with cloud infrastructure such as AWS, Azure, GCP, or DigitalOcean.
Hands-on experience with compute-intensive AI models and repositories such as Stable Diffusion or Llama.
Experience optimizing and deploying AI models for production inference.
Familiarity with transformer-based architectures and their practical applications.
We will be working together on the following:
Developing data pipelines and APIs for AI-powered products and services.
Building scalable and reliable backend systems that serve AI inference results.
Working across AI areas such as data science, image generation, image processing, LLMs, and transformer-based architectures.
Turning research findings and experimental approaches into practical solutions.
Collaborating with AI Product Managers, engineers, and web development teams to translate client needs into technical solutions.
Communicating technical decisions and complex AI concepts to technical and non-technical stakeholders.