Deskripsi pekerjaan Machine Learning Engineer Indonesia Global Solusindo
If you’re excited about working with cutting-edge technologies like FastAPI, RAG, and LLMs, and you enjoy solving complex problems in a collaborative, fast-moving environment, we’d love to hear from you.
Key Responsibilities:
- Design, build, and enhance APIs (using FastAPI) to support both application workflows and large-scale machine learning models.
- Research, prototype, and implement advanced techniques like Retrieval-Augmented Generation (RAG) to connect external knowledge sources with large language models (LLMs).
- Investigate and benchmark new approaches to improve performance, reliability, and overall user experience.
- Collaborate closely with data scientists, backend and data engineers, product managers, and frontend developers to deliver robust, ML-powered product solutions.
- Deploy, monitor, and maintain ML models in production environments, ensuring scalability, stability, and optimal performance.
- Contribute to the design of event-driven architectures (using tools such as Celery, Arq, Google Pub/Sub, or other message brokers) and ensure smooth integration with APIs, databases, and cloud systems.
- Develop and maintain comprehensive unit and integration tests to uphold code quality, reliability, and seamless deployment workflows.
Required Qualifications:
- 2+ years of professional experience as a Machine Learning Engineer or in a related role.
- Strong Python skills and hands-on experience with frameworks such as scikit-learn, PyTorch, Hugging Face, LangGraph, LangFuse, or similar.
- Proven experience implementing RAG pipelines and integrating knowledge bases with LLMs.
- Proficient in FastAPI, API design, SQL/NoSQL databases, and modern data management practices.
- Solid experience with Google Cloud Platform (GCP), Docker, and CI/CD workflows.
- Practical familiarity with Google Pub/Sub or similar messaging systems.
- Demonstrated experience deploying machine learning models into production environments.
Preferred Qualifications
- Familiarity with Golang or Rust for developing performance-critical services.
- Experience optimizing large-scale machine learning pipelines and systems.
- Strong understanding of distributed systems and scalable architecture design.
