Machine Learning Engineer

FactoFlare AI; Bengaluru; Hybrid; INR 2,400,000 - 4,200,000; Full time

Benefits offered by this job

Competitive compensation

Flexible work environment

Job summary

FactoFlare AI in Bengaluru (Hybrid) is seeking a skilled Machine Learning Engineer to bridge research and production by building scalable ML systems powering our Xyranik platform. You will design end-to-end ML pipelines, deploy models at scale, and enable agents to learn and adapt in real-world environments.

Collaborating with research and platform teams, you will implement robust data processing, model serving, and continuous learning infrastructure, while following best practices for

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or related field.
• 3+ years of experience in machine learning engineering or MLOps.
• Strong programming skills in Python and ML frameworks.
• Experience with containerization, orchestration, and cloud computing.
• Understanding of ML system design and deployment best practices.
• Familiarity with data processing frameworks and model serving.

Responsibilities

• Build end-to-end machine learning pipelines for AI agent training
• Deploy and scale ML models for autonomous AI agent systems
• Design infrastructure for continuous learning and model adaptation
• Optimize ML system performance for real-time AI agent operations
• Collaborate with research team to productionize cutting-edge algorithms

Skills

Python

ML frameworks

Data processing

Model serving

Cloud computing

Containerization

Orchestration

ML system design

Education

Bachelor's or Master's degree in Computer Science, Engineering, or related field

Tools

Docker

Kubernetes

Job description

Job Description

Bridge the gap between research and production by building scalable ML systems that power our AI Agentic platform. You'll implement machine learning pipelines, deploy AI models at scale, and ensure our Xyranik agents can learn and adapt in real-world environments.

Home/Careers/Machine Learning Engineer

Machine Learning Engineer

Engineering

Bangalore, India (Hybrid)

Full time

Posted: January 11, 2026

Responsibilities

• Build end-to-end machine learning pipelines for AI agent training
• Deploy and scale ML models for autonomous AI agent systems
• Design infrastructure for continuous learning and model adaptation
• Optimize ML system performance for real-time AI agent operations
• Collaborate with research team to productionize cutting-edge algorithms

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or related field
• 3+ years of experience in machine learning engineering or MLOps
• Strong programming skills in Python and ML frameworks
• Experience with containerization, orchestration, and cloud computing
• Understanding of ML system design and deployment best practices
• Familiarity with data processing frameworks and model serving

Preferred Qualifications

• Experience with AI agent systems and autonomous learning
• Knowledge of feature stores and ML metadata management
• Background in distributed training and large-scale ML systems
• Experience with real-time ML inference and edge deployment

About FactoFlare

FactoFlare is a leading AI technology company focused on developing intelligent solutions that help businesses streamline operations, enhance productivity, and drive innovation. We are committed to creating a diverse, inclusive workplace where all employees can thrive and contribute to our mission of making advanced AI technology accessible and beneficial to organizations of all sizes.

Benefits

• We offer competitive compensation, comprehensive benefits, and a collaborative, flexible work environment that supports both professional growth and work-life balance.

FactoFlare is an equal opportunity employer.

We celebrate diversity and are committed to creating an inclusive environment for all employees.

Job Summary

Department: Engineering

Location: Bangalore, India (Hybrid)

Employment Type: Full-time

Date Posted: January 11, 2026

Additional Information

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