AI/ML Engineer (Databricks)

Company Description
Ironbook AI is a builder-led company focused on solving complex enterprise AI challenges in data activation, agentic automation, and autonomous data engineering. The company operates a dual model, combining AI-native products such as an autonomous data migration agent with a consulting practice that delivers tailored AI solutions for leading enterprises across APAC. Teams work directly with modern cloud ecosystems including AWS, Databricks, Confluent, and MinIO to deploy AI systems at scale. Ironbook AI offers an environment for professionals who want to build meaningful systems, advance the capabilities of AI, and contribute to the future of enterprise technology.
Role Description
The AI/ML Engineer (Databricks) will design, develop, and optimize machine learning pipelines and data workflows on Databricks in a remote, contract role. Day-to-day responsibilities include implementing and tuning ML models, building scalable ETL and feature engineering processes, and integrating these solutions with cloud and data platforms used by enterprise clients. The engineer will collaborate with product and consulting teams to translate business requirements into technical designs, ensure robust model deployment, and monitor performance in production environments. The role also involves contributing to best practices in MLOps, maintaining documentation, and supporting continuous improvement of Ironbook AI’s autonomous data and analytics systems.
Qualifications
Strong foundation in Computer Science and Algorithms, with the ability to design efficient, scalable data and ML solutions. Overall 3 to 5 years of relevant experience using Databricks Data & AI Solutions
Expertise in Pattern Recognition and Neural Networks, including experience training, evaluating, and deploying deep learning models.
Solid grasp of Statistics for model evaluation, experiment design, and data quality assessment.
Hands-on experience with Databricks and modern cloud platforms (e.g., AWS), including Spark-based data processing and ML workflows.
Proficiency in relevant programming languages (such as Python, Scala, or SQL) and common ML libraries and frameworks.
Experience with MLOps practices, including versioning, CI/CD for ML, monitoring, and observability in production environments.
Ability to work independently in a remote setting, collaborate effectively with distributed teams, and communicate complex technical concepts clearly.
Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related quantitative field, or equivalent practical experience.
Prior work on enterprise AI, data engineering, or autonomous data systems is highly beneficial.

Work arrangement
Yes