Machine Learning Engineer

At Smart Working, we believe a job should not only meet expectations on paper but also feel right on a daily basis. This is more than just a remote opportunity; it's about finding a place where you truly belong, regardless of your location. From your first day, you will be part of a supportive community that prioritizes your growth and well-being. Our core mission is to eliminate geographical barriers, connecting skilled professionals with exceptional global teams and products for full-time, long-term positions. We help you find meaningful work with teams that are invested in your success, empowering you to grow both personally and professionally. Join one of Glassdoor's highest-rated workplaces and discover the advantages of thriving in a truly remote-first environment.

About the Role:

As a Machine Learning Engineer, you will be pivotal in architecting, developing, and maintaining production-ready machine learning systems that directly enhance customer experience and commercial outcomes. Your focus will be on deploying low-latency, scalable ML services essential for powering ranking models, recommendation engines, and forecasting solutions across our platform. Working collaboratively with Data Scientists, Product Managers, and Engineering teams, you will bridge the gap between experimentation and production, ensuring models are reliable, resilient, and capable of scaling in a dynamic, data-driven setting. This is a long-term role offering significant ownership, influence, and the opportunity to shape both technical direction and best practices in Machine Learning.

Responsibilities:

• Architect, implement, and maintain production-grade, low-latency ML services for ranking, recommendation, and forecasting use cases.
• Collaborate with data scientists, product managers, and engineers to determine optimal technical approaches for product and infrastructure challenges.
• Design and support experimentation frameworks to test hypotheses and quantify model improvements.
• Provide strategic data advice, ensuring the availability of high-quality, well-structured datasets for current and future data science initiatives.
• Deliver machine learning models that adhere to agreed engineering standards, focusing on scalability, resilience, and long-term maintainability.
• Enhance and evolve an AWS-native MLOps platform, ensuring high availability and low-latency inference.
• Monitor, maintain, and continuously improve deployed models in production environments.
• Contribute positively to team culture through curiosity, ownership, and a bias towards learning and improvement.

Requirements:

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

Nice to Have:

• 1+ year of experience with Snowflake, or substantial 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 optimization.
• Familiarity with AWS-native data or ML tooling.
• Experience 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: Promoting genuine work-life balance.
• Day 1 Benefits: Laptop and comprehensive medical insurance provided from the start.
• Support That Matters: Access to mentorship, community, and forums for idea sharing.
• True Belonging: A long-term career where your contributions are valued.

At Smart Working, you will never be just another remote hire. Become a Smart Worker—valued, empowered, and part of a culture that champions integrity, excellence, and ambition. If this environment resonates with you, we are eager to hear your story. We may utilize Artificial Intelligence (AI) tools to assist in aspects of the hiring process, such as application review or resume analysis. These tools support our recruitment team but do not replace human judgment. All final hiring decisions are made by human personnel. For more information on data processing, please contact us.