AI/ML Engineer

peoplepilot

Bengaluru, India 3 Years Exp Posted 5d ago

Build and ship production models — object detection, segmentation, OCR/text extraction, and classification models behind our products.
Build the AI backend the models live in. Run the models on incoming data, then write the post-processing and pipeline logic that turns raw model output into clean, structured product data. All in Python.
Work in the data layer. Detected and human-corrected results are stored in a document store (MongoDB) — you design document structures and write the queries and aggregations your pipeline and the retraining loop depend on.
Feed the data flywheel — the annotation → correction → retraining loop that makes the models better release over release.
Own evaluation for your work — benchmarks, error analysis, and quality metrics tied to real product outcomes.
Deploy and run your models and your pipeline code — Docker, Kubernetes on AWS EKS — and iterate on what production tells you.
Work under the Principal AI Engineer’s technical direction, and partner with the Senior Applied ML Engineer on data quality and the eval harness.

Location & Work Mode

This role is based in Bengaluru and follows a hybrid work model, with approximately 3 days per week in office and up to 40% work-from-home flexibility.

3–5 years hands-on building production ML/AI — you’ve shipped models that real users or customers rely on.
Strong Python for both model and product code.
Strong PyTorch (or TensorFlow) and solid ML fundamentals.
MongoDB: comfortable designing document schemas and writing non-trivial aggregation queries.
PostgreSQL: working knowledge.
Docker and Kubernetes (AWS EKS), and hands-on AWS experience.

Computer vision (detection/segmentation — YOLO, Detectron2, Mask R-CNN) or OCR / document AI.
Geospatial / GIS exposure (imagery, GDAL/geopandas, remote sensing).
MLOps depth — MLflow, model registry, monitoring, data/label versioning.
RAG / GenAI / agentic exposure, or data-centric ML.
- Fluency with AI-assisted coding.