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Sr Machine Learning Engineer

Sr Machine Learning Engineer

Xoom

5 - 10 years

5 - 8 Lacs

bengaluru

Posted:Just now| Platform:

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Skills Required

unix logistic regression front end linux data modeling shell scripting data processing data quality recruitment sql

Work Mode

Work from Office

Job Type

Full Time

Job Description

This job will design, develop, and implement machine learning models and algorithms to solve complex problems. You will work closely with data scientists, software engineers, and product teams to enhance services through innovative AI/ML solutions. Your role will involve building scalable ML pipelines, ensuring data quality, and deploying models into production environments to drive business insights and improve customer experiences.

Essential Responsibilities

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 Qualifications

Minimum of 5 years of relevant work experience and a Bachelors 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.

Preferred Qualification

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.

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Sr Machine Learning Engineer