Machine Learning Engineer

About Chargebee :

Chargebee is a subscription billing and revenue management platform powering some of the fastest-growing brands around the world today, including Calendly, Hopin, Pret-a-Manger, Freshworks, Okta, Study.com and others. Thousands of SaaS and subscription-first businesses process over billions of dollars in revenue every year through the Chargebee platform.

Headquartered in San Francisco, USA, our 500+ team members work remotely throughout the world, including India, the Netherlands, Paris, Spain, Australia, and the USA.

Chargebee has raised over $480 million in capital and is funded by Accel, Tiger Global, Insight Partners, Steadview Capital, and Sapphire Ventures. And we’re on a mission to push the boundaries of subscription revenue operations. Not just ours, but every customer and prospective business on a recurring revenue model.

Our team builds high-quality and innovative software to enable our customers to grow their revenues powered by the state-of-the-art subscription management platform.

Key Roles & Responsibilities

Productionise ML workflows : build and maintain data pipelines for feature generation, ML model training, batch scoring, and real‑time inference using modern orchestration and container frameworks.

Own model serving infrastructure : implement fast, reliable APIs / batch jobs; manage autoscaling, versioning, and rollback strategies

Feature‑store development : design and operate feature stores and corresponding data pipelines to guarantee training–serving consistency.

CI / CD & DevEx : automate testing, deployment, and monitoring of data and model artefacts; provide templated repos and documentation that let data scientists move from notebook to prod quickly.

Observability & quality : instrument data‑drift, concept‑drift, and performance metrics; set up alerting dashboards to ensure model health.

Collaboration & review : work closely with data scientists on model experimentation, production‑harden their code, review PRs, and evangelise MLOps best practices across the organisation.

Required Skills & Experience

3+ years as a ML / Data Engineer working on large-scale, data-intensive systems in cloud environments (AWS, GCP, or Azure), with proven experience partnering closely with ML teams to deploy models at scale.

Proficient in Python plus one of Go / Java / Scala; strong software‑engineering fundamentals (testing, design patterns, code review).

Hands on experience in Spark and familiarity with streaming frameworks (Kafka, Flink, Spark Structured Streaming)

Hands-on experience with workflow orchestrators (Airflow, Dagster, Kubeflow Pipelines, etc.) and container platforms (Docker + Kubernetes / EKS / ECS).

Practical knowledge of ML algorithms like XGBoost, LightGBM, transformers and deep learning frameworks like pytorch is preferred

Experience with experiment‑tracking / ML model‑management tools (MLflow, SageMaker, Vertex AI, Weights & Biases) is a plus

Benefits :

Want to know what it means to work for a company that genuinely cares about you? Check out just a few of the benefits we give our employees :

We are Globally Local

With a diverse team across four continents, and customers in over 60 countries, you get to work closely with a global perspective right from your own neighborhood.

We value Curiosity

We believe the next great idea might just be around the corner. Perhaps it’s that random thought you had ten minutes ago. We believe in creating an ecosystem that fosters a desire to seek out hard questions, and then figure out answers to them.

Customer! Customer! Customer!

Everything we do is driven towards enabling our customers’ growth. This means no matter what you do, you will always be adding real value to a real business problem. It’s a lot of responsibility, but also a lot of fun.

If you resonate with Chargebee, have a monstrous appetite for curiosity, and an insatiable urge to learn and build new things, we’re waiting for you!

We value people from all backgrounds and are dedicated to hiring and employing a diverse and inclusive workplace.

Come be a part of the Chargebee tribe!