Senior Machine Learning Engineer

At Insignia, we're looking for a Machine Learning Engineer to bridge the gap between data science and production engineering.

You won't just be training models in a notebook. You'll be building scalable pipelines, optimizing inference, and ensuring reliability at scale. If you care about latency, cost, uptime, and making sure your models actually deliver value to the end-user, this is your kind of challenge.

This is a hybrid role based in West Jakarta, where your code powers real-world intelligence.

What You'll Do:

Design, train, and deploy production-grade ML systems from data ingestion to API serving

Build and maintain ML pipelines for training, validation, and continuous serving

Optimize models for performance, cost, and scalability (quantization, batching, caching)

Implement monitoring for data drift, model decay, and system health

Collaborate with data engineers and backend teams to integrate ML seamlessly into products

Establish best practices for MLOps, versioning, and reproducibility

Who You Are:

2–5 years in machine learning engineering or applied AI

Strong in Python, PyTorch/TensorFlow, and modern ML frameworks

Experience with model deployment (FastAPI, Flask, Docker, cloud endpoints)

Familiar with MLOps tools (MLflow, Kubeflow, SageMaker, or similar)

Deep understanding of software engineering principles (testing, CI/CD, system design)

Fluent in English — written and spoken

Pragmatic, systems-oriented, and passionate about building AI that actually works in the wild

Why Join Us

Because great AI isn't measured in papers — it's measured in uptime, user trust, and real-world utility. If you're ready to ship intelligence at scale, let's talk.

Hybrid role – West Jakarta

Tech stack: Python, PyTorch, FastAPI, Docker, AWS/GCP, Git, CI/CD