Machine Learning Engineer (Remote, Full-Time) [AS207] at smart-working-solutions

About Smart Working At Smart Working, we believe your job should not only look right on paper but also feel right every day. This isn’t just another remote opportunity - it’s about finding where you truly belong, no matter where you are. From day one, you’re welcomed into a genuine community that values your growth and well-being. Our mission is simple: to break down geographic barriers and connect skilled professionals with outstanding global teams and products for full-time, long-term roles. We help you discover meaningful work with teams that invest in your success, where you’re empowered to grow personally and professionally. Join one of the highest-rated workplaces on Glassdoor and experience what it means to thrive in a truly remote-first world. About the Role 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. You’ll focus on deploying low-latency, scalable ML services that power ranking models, recommendation systems, and forecasting solutions across the platform. Working closely with Data Scientists, Product Managers, and Engineering teams, you’ll help bridge the gap between experimentation and production—ensuring 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. 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 identify the best technical approaches to product and infrastructure challenges • Design and support experimentation frameworks to test hypotheses and measure improvements to models • Advise on data strategy, ensuring high-quality, well-structured datasets are available for current and future data science initiatives • Deliver machine learning models that meet agreed engineering standards, ensuring scalability, resilience, and long-term maintainability • Enhance and evolve an AWS-native MLOps platform, supporting high availability and low-latency inference • Monitor, maintain, and continuously improve deployed models in production environments • Contribute positively to team culture, demonstrating curiosity, ownership, and a bias toward 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 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 Nice to Have • 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 At Smart Working, you’ll never be just another remote hire. Be a Smart Worker - valued, empowered, and part of a culture that celebrates integrity, excellence, and ambition. If that sounds like your kind of place, we’d love to hear your story.