[Hiring] Machine Learning Engineer @Smart Working Solutions

Role Description

As a Machine Learning Engineer, you will play a critical role in architecting, building, and maintaining production-grade machine learning systems that directly impact customer experience and commercial performance.

• Focus on deploying low-latency, scalable ML services that power ranking models, recommendation systems, and forecasting solutions across the platform.
• Work closely with Data Scientists, Product Managers, and Engineering teams to bridge the gap between experimentation and production.
• Ensure models are reliable, resilient, and ready to scale in a fast-moving, data-driven environment.
• This is a long-term role with strong ownership, influence, and room to shape both technical direction and ML best practices.

Qualifications

• 5+ years of total professional experience, operating at a senior engineering level.
• 3+ years of hands-on experience in Machine Learning, including taking models from experimentation to production.
• 3+ years of experience with Python, writing production-quality, maintainable code.
• 3+ years of experience working with SQL in analytical or data-intensive environments.
• Strong experience building and operating production ML systems, including model serving and monitoring.
• Solid understanding of experimentation, model evaluation, and performance trade-offs in real-world systems.
• Experience working closely with cross-functional teams in a collaborative, product-focused environment.
• Strong engineering mindset, with a focus on scalability, reliability, and future-proof solutions.

Requirements

• 1+ year of experience with Snowflake, or strong experience with modern cloud data warehouses.
• 1+ year of experience with dbt, or hands-on experience building and maintaining analytical data models.
• Experience contributing to or improving MLOps platforms, including CI/CD for ML, monitoring, and inference optimisation.
• Familiarity with AWS-native data or ML tooling.
• Experience working in high-scale, consumer-facing or e-commerce environments.
• A proactive, curious mindset aligned with values such as continuous learning, thoughtful problem-solving, and positive collaboration.

Benefits

• Fixed Shifts: 12:00 PM - 9:30 PM IST (Summer) | 1:00 PM - 10:30 PM IST (Winter).
• No Weekend Work: Real work-life balance, not just words.
• Day 1 Benefits: Laptop and full medical insurance provided.
• Support That Matters: Mentorship, community, and forums where ideas are shared.
• True Belonging: A long-term career where your contributions are valued.