Job Description

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 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) u007C 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.