AI Engineer

Role summary

This opening is for a full-time AI engineering position supporting a client engagement. The work is fully remote and can be done from anywhere. The main focus is building, scaling, and improving AI/ML systems for production use, with an emphasis on efficient large-scale inference and strong performance in high-compute environments.

What you will do

• Build end-to-end AI/ML solutions, including training workflows, deployment pipelines, and inference optimization.
• Maintain and improve high-performance computing infrastructure used for AI workloads.
• Partner with software engineers to embed AI capabilities into live products and services.
• Improve model efficiency using methods such as quantization, pruning, and accelerator-based optimization.
• Explore and apply modern AI/ML approaches to raise accuracy and system efficiency.

Skills and qualifications

You should be comfortable coding in Python and working with major machine learning frameworks such as TensorFlow, PyTorch, or JAX. Experience with distributed processing tools like Apache Spark or Dask is important for handling large data volumes. Familiarity with cloud environments such as AWS, GCP, or Azure, along with Docker and Kubernetes, is expected. Knowledge of deployment and inference tools like ONNX and TensorRT will be useful, as will a solid grasp of algorithms, data structures, and good software engineering practices.

Additional details

This opportunity offers an estimated payout of $160K to $300K per year. The role is intended for candidates who are ready to take on complex technical challenges in collaboration with specialists across AI, engineering, and infrastructure. The hiring approach is skills-first, and qualified candidates are considered regardless of background, prior experience, or employment history.