Description

Qualifications: 
10+ years of IT experience and at least 5+ years working as a Machine Learning Engineer
Must have strong programming skills in Python
Experience with both RDBMS and NoSQL databases (e.g., MongoDB, BigQuery)
Hands-on experience with data preprocessing, feature engineering, and model evaluation
Experience working with cloud platforms, especially Google Cloud Platform (GCP)
Experience with Vertex AI, BigQuery, Pub/Sub
Solid understanding of machine learning concepts, algorithms, and workflows
Nice to Haves :
Experience using Vertex AI or Azure OpenAI Services
Familiarity with Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) workflows
Knowledge of Natural Language Processing (NLP) techniques
Experience working with big data technologies (e.g., Apache Spark, Ray, or Dark)
Exposure to streaming data platforms such as Apache Kafka or Google Pub/Sub
Familiarity with Git or other version control systems
Strong problem-solving skills, attention to detail, and ability to work collaboratively
Candidates should be comfortable building and deploying models in a cloud environment and integrating ML pipelines with other cloud-native tools.
Education & Certifications:
Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related field
Relevant certifications are a plus (e.g., Google Professional Data Engineer, AWS Certified Data Analytics)
Summary:
Strong Python Skills + ML Engineering Experience 
The role is hands-on and requires candidates who have actually built, trained, and deployed ML models—not just theoretical or academic experience. 
Python is the primary language, so fluency here is non-negotiable. Look for real-world experience using libraries like scikit-learn, TensorFlow, or PyTorch

Key Skills

Education

Any Graduate