All roles

Machine Learning·Bangalore, IN

ML Engineer

Mid–Senior

Own the matching, ranking and similarity models powering autonomous entity resolution — and the MLOps that keep them honest at 10M+ records / day.

Entity ResolutionRankingEmbeddingsMLOpsPyTorch

Team

Machine Learning

Location

Bangalore, IN

Experience

5+ years (production ML deployment)

Tech stack

Apply for this role

What you’ll do

01 Build and operate matching, ranking and classification models at scale
02 Design robust feature pipelines on streaming + batch data (Spark, Databricks)
03 Train and serve embedding models for high-recall blocking and similarity scoring
04 Implement explainable score-calibration and confidence-thresholding for steward workflows
05 Build MLOps infrastructure: experiment tracking, model registry, automated evaluation, deploy pipelines
06 Establish drift detection and continuous-evaluation to surface degradation before customers do
07 Collaborate with the AI Engineer on retrieval quality and rerankers
08 Partner with Data Engineering on data contracts and quality

What we’re looking for

→ 5+ years building and operating ML systems in production
→ Strong PyTorch skills — training, fine-tuning and inference optimisation
→ Hands-on experience with one or more of: Spark, Flink, Ray, Databricks, Snowflake
→ Comfortable with SQL at scale and the Python ML stack
→ Strong fundamentals in supervised ML, evaluation metrics and experimentation
→ Proficiency with Hugging Face Transformers, PEFT, Datasets, Evaluate
→ Working knowledge of MLOps: MLflow, Weights & Biases, DVC or equivalent
→ Practical experience with model optimisation: quantisation, distillation, batched inference

Nice to have

ML Engineer · Mid–Senior

Job Description & Responsibilities