Senior Machine Learning Engineer

Overview

Senior Machine Learning Engineer on the Search Scaling team, responsible for running the ML and AI behind Bloomreach search in production, in the live search path and in catalog data pipelines.

What you'll do

• Design, build and operate ML components in the search serving path, within tight latency budgets.
• Build query-time ML that helps search understand and handle each query.
• Build and scale ML and LLM data pipelines across large product catalogs, with attention to cost and freshness.
• Tune models across merchants, verticals and languages.
• Build and scale online features and model serving infrastructure.
• Set up offline evaluation and safe rollout for production models: baselines, A/B tests, fallbacks, and latency and cost tracking.
• Improve observability and diagnosis of ML systems in production.
• Work with Search Quality engineers to bring their models into production within latency and cost targets.
• Contribute to technical design and influence decisions across teams.

What you'll need

• BE/B.Tech/ME/M.Tech in Computer Science or a related discipline, with a strong mathematical foundation.
• Excellent programming skills in Python.
• Experience with a backend language such as Go or Java.
• 5+ years of experience building ML-driven systems in production.
• Strong software engineering skills, with hands-on experience serving ML models and LLMs in scalable cloud systems (AWS/GCP) under tight latency and cost budgets.
• Experience building large-scale data and ML pipelines.
• Strong problem-solving and analytical skills: able to break a problem down into its model-training and backend-engineering parts, and, during development, analyze results to pinpoint the cause of an issue and choose the right next step.
• Experience working across multiple customers, domains or languages.
• Working knowledge of search, such as query understanding, ranking, autosuggest or faceting.
• Experience with deep learning frameworks such as PyTorch or TensorFlow.

Nice to have

• Experience with Solr, Elasticsearch or a similar search engine.
• Experience with vector search in production, such as Milvus or Qdrant.
• Experience building evaluation, observability or explainability tooling for ML models, LLMs and serving systems.

Details

• Location: India.
• Work mode: remote (#LI-Remote); the team works virtual-first with several Bloomreach Hubs across three continents.
• Flexible working hours.