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
This is an exciting opportunity to join a growing Pricing and Analytics function undergoing a major transformation in strategy, tooling, and capability. As a Machine Learning Engineer, you’ll focus on building and maintaining shared tooling and packages that power the analytical lifecycle, enabling teams to deliver value faster, more consistently, and with stronger controls.
The role sits at the intersection of data science and software engineering, with a strong emphasis on improving standards, scalability, and reusability across modelling, analysis, and deployment workflows. You’ll play a key role in increasing both the velocity and long-term value of machine learning and analytics initiatives.
Responsibilities
- Enable the Pricing and Analytics function to deliver value in a seamless, efficient, and controlled way through standardised modelling, analysis, and deployment workflows
- Design, build, and maintain Python-based modelling and ML tooling used across the analytics lifecycle
- Develop metrics and frameworks to assess the value of new models and monitor the ongoing performance and impact of existing ML services
- Support the deployment and operation of data science and machine learning services in production environments
- Raise standards of software engineering, ML engineering, and development practices across the department
- Collaborate with analysts, data scientists, and stakeholders to ensure tooling meets real business and customer needs
Requirements
- Strong experience building and maintaining machine learning or data science tooling in Python
- Solid software engineering foundations, with a focus on clean, reusable, and well-tested code
- Experience supporting or operating machine learning models in production
- Understanding of the end-to-end analytical lifecycle, from experimentation to deployment and monitoring
- Ability to work collaboratively across technical and non-technical teams to enable scalable solutions
- Experience improving or enforcing engineering and ML best practices within a wider analytics function
Nice to have
- Experience designing shared ML frameworks or internal analytics platforms
- Exposure to pricing, insurance, or other highly regulated, data-intensive domains
- Familiarity with model monitoring, value tracking, or ML governance practices
- Experience working in large-scale transformation or modernisation programmes
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.
