Posted:Just now|
Platform:
Work from Office
Full Time
Design, train, and deploy ML/LLM models for use cases like anomaly detection, forecasting, and conversational AI.
Build modular APIs, pipelines, and microservices for inference and automation.
Maintain scalable ML infrastructure, CI/CD pipelines, and observability for model performance.
Automate model retraining, deployment, and validation using AIOps practices.
Develop data pipelines, manage feature stores, and support RAG-based systems.
Collaborate with engineers and product teams to translate business needs into reliable AI solutions.
Contribute to MLOps standards, documentation, and governance.
Bachelors or Masters in Computer Science, Engineering, or related field. And willing to relocate to Indonesia if needed.
5+ years of experience in backend or ML engineering
Strong Python skills (FastAPI, Flask) and microservice architecture knowledge
Hands-on experience deploying and monitoring ML/LLM models in production
Proficiency with ML frameworks (PyTorch, TensorFlow, Hugging Face, LangChain)
Familiar with infrastructure tools (Docker, Kubernetes, Terraform, Airflow) and cloud platforms (GCP/AWS/Azure)
Understanding of observability (Prometheus, Grafana, ELK, OpenTelemetry) and vector databases (Pinecone, Weaviate, FAISS)
Experience managing GPU workloads and optimizing cost
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