Machine Learning Solutions Engineer (Backend & Customer Solutions)

Role Overview

We are looking for a proactive Machine Learning Solutions Engineer who combines strong backend development skills with practical experience in machine learning. The ideal candidate will contribute to backend and AI development while acting as the technical point of contact for customer-facing technical issues.

Responsibilities

• Design, develop, and maintain Python-based backend services.
• Build, optimize, and deploy machine learning pipelines.
• Develop backend systems supporting AI-driven products.
• Monitor, troubleshoot, and improve production performance.
• Support integration of ML models into production.
• Act as the technical escalation point for customer issues.
• Investigate backend, application, and ML-related issues.
• Analyze logs and model outputs to identify root causes.
• Work closely with Customer Support to provide technical resolutions.
• Join customer calls to understand issues and explain solutions.
• Coordinate with engineering teams to resolve technical issues.
• Identify recurring issues and recommend product improvements.
• Collaborate with Product, QA, Customer Success, and Engineering teams.
• Document investigations and technical solutions.
• Support production releases and operational activities.
• Develop troubleshooting guides and knowledge base documentation.

Requirements

• Strong programming skills in Python.
• Strong understanding of backend application development.
• Good understanding of machine learning concepts.
• Experience working with SQL and databases.
• Excellent analytical and problem-solving skills.
• Strong communication and stakeholder management skills.
• Ability to interact with customers and understand technical requirements.
• 2–5 years of relevant industry experience.
• Hands-on experience with production AI/ML systems is preferred.

Nice to Have

• Exposure to Computer Vision or image processing.
• Experience with OpenCV or similar libraries.
• Knowledge of cloud platforms (AWS, Azure, or GCP).
• Exposure to Docker and CI/CD.
• Experience with production support and monitoring tools.

Skills

• Python
• SQL
• Machine Learning
• Docker
• AWS

Benefits

• Paid sick time
• Provident Fund