Experience: 5–8 Years
Location: Bangalore
Engagement: C2C | Duration: 3 Months
Budget: ₹2–2.5 LPM
UAN: Mandatory
Role Overview
We are looking for a skilled Machine Learning Engineer to design, build, and maintain ML pipelines and production-grade systems with a focus on NLP and end-to-end ML lifecycle management on GCP.
Must-Have Skills
- Strong in Python, Java, and Advanced SQL.
- Hands-on experience with GCP (preferred) and Docker.
- Experience with Vertex AI Pipelines, Airflow, or other orchestrators.
- Solid understanding of ML lifecycle, data engineering, and feature engineering.
- Proficient with TensorFlow/PyTorch, FastAPI, and ML model monitoring.
- Experience with distributed computing using Apache Spark, Beam, or Flink.
- Strong knowledge of CI/CD pipelines, Terraform, and Infrastructure as Code.
- Exposure to Kubernetes, Vector Databases (e.g., Qdrant), and LLMs (RAG, embeddings, agents).
Good-to-Have Skills
- Hyperparameter tuning experience.
- Hands-on experience with GCP tools including BigQuery, Cloud Storage, Cloud Spanner, Cloud Dataproc, and Pub/Sub.
- Familiarity with cluster/pipeline optimization and data architecture design.
- Business understanding of data used for BI and analytics.
