ML Engineer · Mid–Senior

Think Right Advisory Services Pvt. Ltd.; Bengaluru Urban; Hybrid; INR 4,000,000 - 7,000,000; Full time

Job summary

Think Right Advisory Services Pvt. Ltd. in Bangalore, IN, is seeking an ML Engineer (Mid–Senior) to own the matching, ranking and similarity models powering autonomous entity resolution and the MLOps that keep them honest at 10M+ records per day.

You will work with PyTorch, Hugging Face, Spark, Databricks, and cloud platforms to build scalable ML systems, design robust feature pipelines, and deploy end-to-end ML workflows in a hybrid environment.

Qualifications

• 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.

Responsibilities

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

Skills

5+ years production ML deployment

PyTorch

Hugging Face

SQL

Python

Tools

Databricks

Spark

Snowflake

MLflow

Weights & Biases

DVC

LoRA

QLoRA

PEFT

AWS SageMaker

GCP Vertex AI

Job description

• Full-time
• Hybrid·5+ years (production ML deployment)

All roles

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

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, batched inference

Nice to have

• MDM / entity-resolution domain experience
• Graph ML or recommendation‑system background
• Experience deploying models on AWS SageMaker, GCP Vertex AI or equivalent