India onlyAbout 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 a critical, hands-on role at the heart of product and client delivery, reporting directly to the Head of ML. You’ll work across three pillars: running ML Ops processes, refining LLM/ML models with human feedback and performance analysis, and transforming conversation data into repeatable, business-ready insights for clients and ongoing model innovation.
As a Machine Learning Data Engineer, you’ll combine technical skills in Python, SQL, BI, and ML Ops with analytical storytelling that bridges data and decision-making. To succeed, you’ll bring an analytical, meticulous, and bias-aware mindset, communicate clearly with non-technical stakeholders, collaborate closely with product and engineering teams, and demonstrate adaptability, initiative, and strong time management in a distributed environment.
Responsibilities
- Insight & research
- Perform hypothesis-led analysis over large datasets to uncover trends, drivers, and client-ready narratives.
- Build and maintain industry benchmark datasets that power reports and dashboards, with tight definitions and version control.
- Deliver clear, actionable Power BI reports for clients and internal stakeholders; maintain stand-alone reports in third-party tools where required.
- ML Ops lifecycle (operate & improve)
- Own performance dashboards, operational processes, model registry/version control, and experiment tracking.
- Monitor drift and bias, validate improvements, and manage safe deployment/rollback.
- Keep the feature store up to date, ensuring training data lineage and reproducibility.
- Partner on productised evaluations (automated tests, acceptance thresholds) and bias mitigation aligned to policy.
- Product & data engineering
- Specify, design, and implement dashboards and reports, integrating with portals and APIs.
- Collaborate with platform/DB teams on robust data integration and storage patterns across PostgreSQL/NoSQL and data lake assets.
- Support Copilot auto-report creation, ensuring source-of-truth metrics and governance.
- Client analysis
- Run client-specific studies to test hypotheses and meet project goals.
- Present findings clearly to non-technical audiences.
Requirements
- Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field
- 3–4 years of experience in data analysis, BI, or ML analytics
- Python (pandas, NumPy, scikit-learn): 3+ years, with strong SQL skills. (R is an advantage.)
- Power BI (data models, DAX): 2+ years, including Power Query (M) and advanced Excel (pivots, complex formulas)
- Data warehousing & ETL: 2+ years, including statistics for A/B testing, sampling, and bias checks
- Databases: PostgreSQL, DynamoDB (or equivalent)
- Familiarity with LLM concepts and evaluation methods
- Exposure to cloud data services (AWS/Azure) and ML Ops tooling (feature store, experiment tracker, model registry, monitoring)
Nice to have
- Healthcare or life sciences exposure
- Relevant BI/analytics certifications (e.g., Microsoft Data Analyst)
- Experience with advanced ML Ops practices
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.
