bengaluru karnataka pharma production Jobs – 84 Open Jobs Today

Data Science II - ML Ops
ProcDNA —Bengaluru, Karnataka
- Full-time
- Azure
- Master's degree
- SQL
SAP PP Consultant
Thoucentric —Bengaluru, Karnataka
- Full-time
- Hybrid work
- Analysis skills
- Agile
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- Azure
- Salesforce
- Master's degree
Data Science II
ProcDNA —Bengaluru, Karnataka
- Full-time
- Azure
- Microsoft Office
- SQL
Project Engineer
ABB —Bengaluru, Karnataka
- Online application
- Engineering
- English
- Machine learning
S&C GN - MC - Industry X - Production & Operations - Analyst
Accenture —Bengaluru, Karnataka
- Full-time
- Azure
- Salesforce
- Master's degree
Sr.Manager-Downstream Planning
Schneider Electric —Bengaluru, Karnataka
- Online application
- Microsoft Excel
- Oracle
- Engineering
Data Tester
Endpoint Clinical —Bengaluru, Karnataka
- Full-time
- Hybrid work
- Computer Science
- SQL
- Analysis skills
Incorta Admin
Estuate —Bengaluru, Karnataka
- Full-time
- Oracle
- SQL
- Scripting
Senior Software Packager
Merative —Bengaluru, Karnataka
- Full-time
- Computer Science
- Software troubleshooting
- Windows
- Health insurance
- Paid time off
1d
Principal Engineer - Backend
Unifize —Bengaluru, Karnataka
- ₹60,00,000 - ₹70,00,000 a year
- Full-time
- Presentation skills
- Bachelor's degree
- APIs
Quick apply
CRM Developer
Takeda Pharmaceutical —Bengaluru, Karnataka
- Full-time
- Salesforce
- APIs
- Agile
- Health insurance
- Cell phone reimbursement
Associate
PwC —Bengaluru, Karnataka
- Full-time
- Azure
- Computer Science
- Salesforce
Executive –Retail Stores Expansion
Atya Ebiz Solutions LLP —Bengaluru, Karnataka
- ₹45,000 - ₹50,000 a month
- Full-time
- Sales
- In-person
- Negotiation
- Paid time off
- Cell phone reimbursement
Quick apply
Webinar Expert
Astellas —Bengaluru, Karnataka
- Hybrid work
- Marketing
- English
- Project management
- Work from home
Databricks Data Engineer - Bengaluru (Hybrid/Remote)
Informica Solutions —Bengaluru, Karnataka
- Full-time
- Remote
- Azure
- Salesforce
- DevOps
Quick apply
Sr. Associate III, ERP Business Analysis
Alcon —Bengaluru, Karnataka
- Full-time
- ERP systems
- Master's degree
- Bachelor's degree
Opcenter Execution core Developer
Snic Solutions —Bengaluru, Karnataka
- Full-time
- Hybrid work
- APIs
- Manufacturing
Quick apply
Senior Manager - AI and Data Governance
Körber AG —Bengaluru, Karnataka
- Azure
- English
- AI
S&C GN - MC - Industry X - Production & Operations - Manager
Accenture —Bengaluru, Karnataka
- Full-time
- Azure
- Salesforce
- Master's degree

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Data Science II - ML Ops

ProcDNA
Bengaluru, Karnataka

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Job details

Full-time

Qualifications

TensorFlow
CI/CD
Cloud infrastructure
Azure
Law
EHR systems
Kubernetes
Big data
Software deployment
Spark
Git
Master's degree
Bash (Unix shell)
SQL
AWS
Docker
Bachelor's degree
Terraform
Continuous integration
REST
Scripting
Unity
GitHub
APIs
Linux
Data science
AI
Python
Shell Scripting

Full job description

Description :
We are looking for an MLOps Engineer with 3â€“5 years of experience building and operating production ML systems, with meaningful exposure to the pharma or healthcare domain. You will be responsible for taking data science outputs and making them robust, scalable, and maintainable in production, covering the full lifecycle from pipeline orchestration and model deployment to monitoring, retraining, and compliance across client engagements.

You will work closely with data scientists, data engineers, and business stakeholders to bridge the gap between experimental models and production-grade systems. Experience navigating regulated or DG-sensitive environments is a strong plus.

Key Responsibilities:

Own and operate end-to-end ML pipelines from feature engineering and training runs through deployment, monitoring, and scheduled retraining, on cloud infrastructure (AWS, Azure, or GCP).
Implement and maintain CI/CD pipelines for ML workflows, ensuring reproducibility, version control of models and data, and reliable rollback capabilities.
Build and orchestrate ML and data pipelines using tools like Airflow, Prefect, or similar; manage dependencies, scheduling, and failure handling.
Build, manage, and govern ML workflows on Databricks, including Jobs, Delta Live Tables, and Unity Catalog, as the primary platform for data and ML pipeline execution.
Manage the full model lifecycle using MLflow on Databricks: experiment tracking, model registry, versioning, stage transitions, and lineage documentation.
Design and deploy ML pipelines on Kubernetes using Kubeflow Pipelines for clients who operate outside Databricks environments, including pipeline authoring, component containerization, and run management.
Leverage pre-trained models, foundation models (LLMs), and cloud AI services instead of building models from scratch where appropriate; implement RAG pipelines, prompt engineering workflows, and evaluation frameworks.
Containerize and deploy models as scalable APIs or batch inference services using Docker and Kubernetes (or managed equivalents); define SLAs and monitor adherence.
Instrument production models for performance drift, data quality degradation, and upstream schema changes; define alerting and intervention protocols.
Collaborate with data scientists to translate experimental notebooks into maintainable, testable, production-ready code.
Maintain experiment tracking and model registries (MLflow or equivalent); enforce model lineage and reproducibility standards.
Partner with data governance and compliance teams to ensure ML pipelines meet audit, traceability, and access-control requirements relevant to pharma/healthcare data.
Participate in code reviews, architecture discussions, and documentation, raising the engineering bar across the DS/ML team.
Develop visualization layers and support self-service analytics platforms.

Required Skills & Qualifications:

3â€“5 years of hands-on MLOps or ML engineering experience in a production environment.
Bachelors or masters
Strong proficiency in Python with experience in packaging, testing, and generating production-grade code. Along with comfortability in handling complex querying across big data through SQL/PySpark
Hands-on experience in Databricks with Jobs, Delta Lake, Unity Catalog, and the Databricks ML runtime beyond Spark compute. Additionally experience with MLflow on Databricks for experiment tracking, model registry (including Unity Catalog-backed registry), lifecycle management, and model serving.
Docker, Kubernetes or equivalents for containerization and scalable model serving.
Experience authoring, deploying, and managing ML pipelines on Kubeflow; comfortable working within existing Kubernetes clusters on client infrastructure.
Design and implement agent-based or orchestration-driven AI workflows using frameworks such as LangChain, LangGraph, or cloud-native equivalents.
CI/CD pipelines for ML workflows (GitHub Actions, Azure DevOps, or equivalent).
REST API design and deployment of model-serving endpoints.
Experience with Cloud platforms (AWS, Azure, or GCP) for infrastructure management and managed ML services.
Model monitoring, drift detection, and alerting in production.
Git and version control best practices; Linux and Bash scripting.

Nice to have

SageMaker, Vertex AI, or other managed ML platforms.
OpenShift or other enterprise Kubernetes distributions commonly found in pharma client environments.
Sufficient depth of understanding with scikit-learn, XGBoost, PyTorch, or TensorFlow, to debug and optimize what data scientists hand over.
Terraform or IaC tooling for ML infrastructure.
OMOP, FHIR, or HL7 familiarity.
Awareness of 21 CFR Part 11, GxP, or audit trail requirements in pharma ML contexts.
LLM/GenAI pipeline experience: prompt versioning, evaluation, latency monitoring.

Apply Now

Refine Your Search

pharma production jobs in bengaluru karnataka

Data Science II - ML Ops

SAP PP Consultant

S&C GN - MC - Industry X - Production & Operations - Consultant

Data Science II

Project Engineer

S&C GN - MC - Industry X - Production & Operations - Analyst

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Principal Engineer - Backend

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Senior Manager - AI and Data Governance

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