Y-Axis Jobs Logo
Send us feedback
telephone  +91 7670 800 001
Log in Sign up Try Premium
Sr Machine Learning & AI Engineer at PayPal
Bengaluru, karnataka, India -
Full Time

Start Date

Immediate

Expiry Date

07 Jan, 26

Salary

0.0

Posted On

09 Oct, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Machine Learning, AI Engineering, Data Processing, Model Deployment, Cloud Platforms, Python, Java, Scala, Unix/Linux Shell Scripting, Big Data Technologies, Data Modeling, Feature Engineering, SQL, ETL Processes, Containerization, Distributed Systems

Industry

Software Development

Description
Develop and optimize machine learning models for various applications. Preprocess and analyze large datasets to extract meaningful insights. Deploy ML solutions into production environments using appropriate tools and frameworks. Collaborate with cross-functional teams to integrate ML models into products and services. Monitor and evaluate the performance of deployed models. Minimum of 5 years of relevant work experience and a Bachelor's degree or equivalent experience. Experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn. Familiarity with cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment. Several years of experience in designing, implementing, and deploying machine learning models. Advanced proficiency in multiple programming and scripting languages, including Python, Java, Scala, and Unix/Linux Shell Scripting. Demonstrated expertise in designing, implementing, and deploying end-to-end AI/ML solutions in production environments on On-Prem and Cloud (GCP, AWS, or Azure). Hands-on experience with Big Data technologies such as Hadoop, Spark, HBase, and Kafka. Expertise in data modeling, feature engineering, and a strong grasp of traditional machine learning algorithms (e.g., Neural Networks, Linear Regression, Logistic Regression, Random Forest, etc.). Experience with Large Language Models (LLMs), particularly in areas like RAG, MCP, and Agentic Agents. Experience in containerization tools like Docker and Kubernetes. GCP experience is a distinct advantage. Strong proficiency in SQL, ETL processes, and database design, with practical knowledge of NoSQL systems like HBase, Redis, and Aerospike. Solid understanding of distributed systems, real-time data streaming, and complex event processing architectures. Knowledge of front-end and back-end development; full-stack engineering experience is a plus.
Responsibilities
Develop and optimize machine learning models for various applications. Collaborate with cross-functional teams to integrate ML models into products and services.