Bahadurgarh, Haryana Mlops / ml engineer Jobs – 12 Open Jobs Today

ML Engineer (CONTRCAT)
Employe Hub —Delhi, Delhi
- ₹3,98,175.91 - ₹16,52,806.44 a year
- Part-time
- Azure
- Computer Science
- Salesforce
Quick apply
Senior MLOps / ML Engineer
Employee Hub LLP —Delhi, Delhi
- Up to ₹12,00,000 a year
- Azure
- Computer Science
- Salesforce
Quick apply
Data Scientist (Contract6 month)
Employe Hub —Delhi, Delhi
- ₹6,00,436.05 - ₹19,75,141.93 a year
- Part-time
- Azure
- Salesforce
- Engineering
Quick apply
MLOps Engineer
NTT DATA —Delhi, Delhi
- Full-time
- Azure
- Computer Science
- DevOps
Machine Learning & LLM Engineer
L.E.K. Consulting —Delhi, Delhi
- Full-time
- Hybrid work
- Azure
- DevOps
- Master's degree
4d
MLOps Engineer
NTT Ltd —Delhi, Delhi
- Full-time
- Azure
- Computer Science
- DevOps
Associate – ML Engineer (Data Business CoE)
Bain & Company Inc —Delhi, Delhi
- Full-time
- Master's degree
- SQL
- AWS
AI Engineer (Fresher) – Mobile Radio Tester
ROHDE & SCHWARZ GmbH & Co. KG —Delhi, Delhi
- Online application
- Remote
- Azure
- Doctoral degree
- Computer Science
- Health insurance
Senior Machine Learning Operations Engineer
Siemens —Delhi, Delhi
- Full-time
- Hybrid work
- Computer Science
- DevOps
- Master's degree
DevOps Engineer - Tech and AI
Council on Energy, Environment and Water —Delhi, Delhi
- Full-time
- Computer Science
- DevOps
- Master's degree
Data Science Engineer (AI)
Consilium Software —Delhi, Delhi
- Azure
- Databases
- SQL
Sr. AI engineer (Remote)
Sezzle —Delhi, Delhi
- ₹50,000 - ₹1,20,000 a year
- Full-time
- Remote
- Computer Science
- Databases
- SQL

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Senior MLOps / ML Engineer
Employee Hub LLP —Delhi, Delhi
*Monitoring & Reliability:* Implement model monitoring (performance, data/concept drift, alerting) to ensure maximum uptime in plant settings.
Up to ₹12,00,000 a year
Quick apply
Global Data Science Senior Manager – Chapter Lead
Boston Consulting Group —Gurugram, Haryana
In this role, you’ll work closely with internal stakeholders to design and deliver data-driven, visualization, and innovation solutions that enhance decision-…

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ML Engineer (CONTRCAT)

Employe Hub
Delhi, Delhi

Quick apply

Job details

Part-time | Full-time
₹3,98,175.91 - ₹16,52,806.44 a year

Qualifications

CI/CD
Azure
Computer Science
Kubernetes
Enterprise Software
SAP
Salesforce
Spark
ERP systems
Git
Master's degree
SQL
Pandas
OOP
AWS
Docker
Bachelor's degree
Continuous integration
APIs
Distributed control systems
Kafka
Manufacturing
Flask
Cybersecurity
SAP ERP
Python

Full job description

[3:42 pm, 17/6/2026] Megha: About the role:

You are the engineer who turns models into reliable production systems running against live plant and enterprise data. You own the path from notebook to production — deployment, monitoring, retraining — including the demanding case of models that feed back into plant control systems where stability and latency are non-negotiable. Without this role, pilots never industrialise.

Key responsibilities

Build and own CI/CD pipelines for ML; package, deploy and serve models in production (batch, real-time, and edge / on-prem as plant environments demand).

Stand up and maintain MLOps infrastructure — experiment tracking, model registry, feature pipelines and automated retraining.

Implement model monitoring (performance, data and concept drift, alerting) and ensure reliability and uptime in plant settings.

Integrate models with operational systems — DCS / control systems for advisory and closed-loop use, plant historians — and with enterprise systems (SAP, Salesforce).

Build robust data pipelines feeding the lakehouse from both OT and IT sources.

Partner with data scientists to productionise their work, and with platform / security teams on OT/IT integration and cybersecurity.

Champion engineering best practices: testing, versioning, reproducibility and documentation.

Required qualifications (must-have)

Bachelor's or Master's in Computer Science, Engineering, or a related field.

3–6 years in ML engineering, MLOps, data engineering or software engineering with production ML exposure.

Strong Python software-engineering fundamentals — OOP, type hints, automated testing (pytest), packaging, clean modular code, and version control.

Solid working command of classical ML (scikit-learn pipelines, regularised regression,

tree-based ensembles, clustering) — enough to package, serve, optimise and monitor these models reliably in production.

Hands-on with containerisation (Docker), orchestration (Kubernetes) and workflow tools (Airflow / Prefect / Dagster).

Experience with MLOps tooling (MLflow, Kubeflow, SageMaker, Azure ML or similar) and model serving.

Cloud experience (Azure, AWS or GCP) and a modern data stack (Spark / Databricks).

CI/CD (Git-based pipelines) and familiarity with infrastructure-as-code.

Preferred (strong pluses)

Experience deploying ML in industrial / manufacturing settings, including edge or on-prem deployment near plant equipment.

Exposure to OT / IIoT integration — plant historians, OPC-UA, time-series databases, streaming (Kafka).

Integration experience with SAP (ERP) and Salesforce (SFDC) data and APIs.

Real-time / streaming ML and model optimisation for low latency.

Awareness of OT cybersecurity considerations.

Technical skills

Python software engineering: advanced, production-grade Python — OOP, type hints, automated testing (pytest), packaging & dependency management, profiling and performance; building model APIs with FastAPI / Flask; strong SQL and Git.

Classical ML in production: working command of scikit-learn pipelines and classical models (regularised regression, tree-based ensembles — XGBoost / LightGBM, clustering); model serialisation (joblib / pickle / ONNX); batch and real-time inference.

Data engineering: pandas and PySpark for batch processing; streaming with Kafka; data validation (pydantic, Great Expectations); feature pipelines / feature stores.

MLOps & infrastructure: Docker, Kubernetes, MLflow, Airflow / Prefect, CI/CD and infrastructure-as-code; model registries and serving frameworks.

Platform & tooling

Cloud (Azure / AWS / GCP); Databricks / Spark; time-series databases and historian / OPC-UA connectors.

Pay: ₹398,175.91 - ₹1,652,806.44 per year

Work Location: In person

Quick apply

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mlops / ml engineer jobs in bahadurgarh, haryana

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Sr. AI engineer (Remote)

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