Where this role is available
Collapsed by default to keep the job description easy to scan.
- Malaysia, Malaysia
- Malaysia
Role summary by JobGrid
Power ML Engineer at kpler: Malaysia, Malaysia, Malaysia; On-site. JobGrid adds normalized role facts, source context, and a path to the employer application page so candidates can compare the listing before applying.
- Location and workplace: Malaysia, Malaysia, Malaysia, On-site
- Source freshness: checked by JobGrid on 2026-05-30.
- Application path: candidates continue to the employer application page with non-personal referral tags.
Key Responsibilities
Learn and adapt existing models to the Japanese market
Integrate market signals from other commodities (LNG, coal) to enhance the quality of our forecasts
Enrich the product and participate in the development of new features
Build and improve monitoring and alerting tools and dashboards
Ensuring good performance on our API to distribute the data to end users
Discuss the roadmap in collaboration with the product team. Help the team build ambitious yet sustainable plans
Experience & Background
Understanding of electricity grid fundamentals (Production, Transmission, Markets)
Circa 3-5 years' of experience as a data focused Software Engineer
Significant experience working with Python (FastAPI is a plus)
Have worked with with Postgresql or similar data stores,
Proficiency in building and consuming RESTful APIs
Machine Learning research (Training, Evaluation, Backtesting, Tuning, Model selection). Deep learning is a plus, but not required
Data Science research (Stats, Hypothesis testing…)
ML Engineering (model versionning, feature versionning)
Comfortable working with Git, code reviews, and Agile methodologies
Experience with time-series, events data, normalization, database design
Strong command of written and spoken English
Understanding of performance optimization and caching strategies
Previous experience in electricity markets
Have experience with AWS (or another cloud provider), using Terraform
Experience with orchestration tool Airflow on a production environment
Experience with containerization (Docker) and orchestration (Kubernetes)
Experience with a ML registry framework (e.g. MLFlow…)
Knowledge on hexagonal architecture and medallion architecture
Used monitoring solutions (Datadog, Grafana, etc...)
Experience with NoSQL database
Japanese speaker
Skills & Competencies
Great communication, ability to work asynchronously with team members in other countries
Curious to learn about the domain
Qualifications
- BSc/MSc in computer science, computer engineering or equivalent