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Machine Learning·Bangalore, IN

• BHIVE Workspace, AKR Tech Park (Kudlu Gate)
• Full time
• Hybrid·5+ years (production ML deployment)

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

• BHIVE Workspace, AKR Tech Park (Kudlu Gate)

Experience

5+ years (production ML deployment)

Tech stack

• PyTorch
• Hugging Face
• Spark
• Databricks
• Snowflake
• MLflow
• W&B;
• DVC
• LoRA
• QLoRA
• PEFT
• AWS SageMaker
• GCP Vertex AI

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, ba

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