[MHT] Machine Learning Engineer Lead

DANA Indonesia is currently looking for a skilled and highly motivated Machine Learning Engineer to join our team!

Machine learning engineers turn models into software. they divide their time between development and maintenance of a deployed machine learning pipelines, developing new machine learning pipelines, and improving the scalability and reliability of a running machine learning modules. 

Our machine learning engineers concentrate on how we can confidently deliver machine learning pipelines on a scale that is required to support DANA ecosystems. They are working tightly together with technical-minded people such as software engineers, devops engineers, and data engineers to ensure smooth integration between various systems.

Some work that our machine learning engineers did include: 

• Design and setup a unified and scalable machine learning architecture that can be applied to all data products 

• Develop reusable machine learning pipeline components 

• Brings model inference from experiment phase into production phase so that other DANA systems can consume prediction result in either batch or online process. 

Key Responsibilities 

• Lead the design, development, and maintenance of scalable machine learning architectures and pipelines. 

• Mentor and guide junior machine learning engineers, promoting best practices and technical excellence. 

• Ensure seamless integration of machine learning models into production environments. 

• Collaborate closely with cross-functional teams to align machine learning solutions with business goals. 

• Stay current with the latest advancements in machine learning and related technologies, and drive their adoption within the team. 

Qualifications 

• Minimum of 5 years of experience in machine learning engineering or related fields. 

• Proven track record of bringing machine learning models to production. 

• Strong programming skills in languages such as Python, and proficiency with machine learning frameworks like PyTorch. 

• Experience with data processing tools like Apache Spark and orchestration tools like MLflow. 

• Excellent problem-solving skills and the ability to work independently. 

• Strong communication skills and the ability to work collaboratively with remote teams.