Applied AI Engineer

About the role

We are seeking an Applied AI Engineer to own the definition, scaling, and expansion of AI/ML solutions at Redpine. You will develop and implement machine learning models that power our platform, enabling organizations to source, validate, and manage high‑quality training and inference data.

Key responsibilities

• Design and implement machine learning models for data quality assessment and validation.
• Develop algorithms for automated data labeling and annotation verification.
• Create and maintain data processing pipelines for various AI training data types.
• Develop and optimise matching algorithms between data providers and buyers.
• Implement scalable solutions for processing and analysing large datasets.
• Collaborate with the product team to add new features to the marketplace platform.
• Research and apply state‑of‑the‑art ML techniques for data quality improvement.
• Work with customers and stakeholders to understand data requirements for diverse AI use cases.

Required profile

• Strong experience developing, training, and deploying AI/ML models.
• Proficiency in Python and ML frameworks such as PyTorch, R, Scala, and Hugging Face.
• Knowledge of model deployment and serving frameworks like TensorFlow Serving, TorchServe, or custom APIs.
• Experience with large‑scale data processing and distributed computing.
• Experience with containerisation and orchestration tools (Docker, Kubernetes) and version control (Git).
• Excellent communication skills and ability to work in a fast‑paced environment.
• Ability to write queries, explore data, and collaborate on hypotheses with product and engineering teams.
• Proficiency in independently setting up and managing cloud services for global scaling.
• A Master’s or Ph.D. in Computer Science, Machine Learning or a related field is a plus.

Required skills

• Python
• PyTorch
• R
• Scala
• Hugging Face
• TensorFlow Serving
• TorchServe
• Docker
• Kubernetes
• Git

What we offer

• Competitive salary and meaningful equity.
• Small team with high ownership; the same people design, ship, and run the systems.
• Office‑first environment with autonomy for deep‑work days and relocation support.