Posted today · be early
Senior Software Engineer (Machine Learning)
Maropost
IndiaremotePosted today
Skill Required
Machine-Learning-EngineerSoftware-EngineerAI-EngineerSenior-Software-AI-EngineerSenior-AI-Software-EngineerSenior-ML-EngineerSenior-AI-ML-EngineerSenior-Machine-Learning-Backend-EngineerSenior-ML-EngineeringDeveloperMachine Learning EngineerSoftware EngineerSoftware DeveloperMachine LearningEmail MarketingComputer VisionScikit-learnStatisticsKubernetesanalyticalautomationbuildingXGBoostPostgreSQLGitHub ActionsFastAPIPyTorchPrometheusPythonPandasDockerArgoCDdesignNumPyKafkaFlinkMySQLRedisFulltime
Key highlights
- Required experience: 5+ years building ML systems (3+ years serving live traffic)
- Key requirement: Hands-on recommender systems or search ranking experience
- Notable requirement: Willingness to own deployments (Docker/Kubernetes)
Role overview
Maropost offers a unified commerce experience transforming ecommerce, retail, marketing automation, merchandising, helpdesk and AI operations with one platform designed to scale for fast-growing businesses. You will own the machine learning that powers product discovery for merchants, including personalized search ranking, recommendation widgets, email recommendations, and an LLM shopping assistant. This is an end-to-end role where you will train models, build the services that serve them, and keep both running in production.
Responsibilities
- Design, train and ship recommendation and ranking models - session-based embeddings, collaborative filtering, content and visual embeddings.
- Build and operate the Python services that serve them at low latency.
- Run the batch pipelines that rebuild model artifacts daily across hundreds of merchants.
- Design and read AB tests; decide what ships on the evidence.
- Own your deployments: containers, Kubernetes manifests, autoscaling, dashboards, alerts.
- Extend our LLM work - a shopping assistant and LLM-assisted catalogue enrichment - with proper evaluation behind it.
Requirements
- 5+ years building machine learning systems, with at least 3 years of models serving live production traffic.
- Strong Python,(FastAPI or equivalent).
- Vector databases (Qdrant).
- Other ANN libraries - FAISS, Annoy, ScaNN. HNSWlib is what we run, but the trade-offs transfer.
- Hands-on recommender systems or search ranking experience: implicit feedback, embeddings, approximate nearest neighbour search.
- Solid SQL against analytical stores.
- Comfortable with Docker and Kubernetes, and willing to own the deployment of your own work.
- Experience running AB tests and reporting results you did not like.
- Streaming systems (Pulsar, Kafka, Flink)
- Exemplify Maropost’s Values: Customer Obsessed, Extreme Urgency, Excellence, Resourceful
Nice to have
- ClickHouse experience
- PyTorch, sentence-transformers and CLIP, or computer vision applied to product imagery.
- Gradient boosting for ranking (XGBoost, LightGBM or CatBoost).
- Scikit-learn and scipy for lightweight classifiers and experiment statistics.
- LLM application work with evaluation harnesses, tool calling, and cost and latency tuning.
- E-commerce, search relevance, or marketplace background.
- Python async experience
- Experience around search
Additional details
- Recommendations are re-ranked in the live request path for storefronts, under a 200 ms budget, measured by merchant conversion.
- Our stack: Python 3.11–3.13, FastAPI, gensim, PyTorch, sentence-transformers and CLIP, HuggingFace transformers, XGBoost, scikit-learn, scipy, pandas, numpy, HNSWlib, Qdrant, ClickHouse, Redis, MySQL, Postgres, Pulsar, Docker, Kubernetes on GCP, ArgoCD, CircleCI, Grafana, Sentry, and Gemini on Vertex via pydantic-ai.
- Message from the Founders: Maropost is looking for builders - people who want to drive our business forward at all costs in order to achieve the goals we have both short and long term for the results and outcomes that that will bring to us all.
- Originally posted on Himalayas
