Job Description
Dear all,
We’re Hiring: Machine Learning Engineer (ML Ops / Production Cloud Development & Sustainment)
Company: SRS Infoway
Job Position: Machine Learning Engineer – ML Ops / Production Cloud
Work Mode: Hybrid
Job Location: Bengaluru, Karnataka, India
SRS Infoway is looking for an experienced Machine Learning Engineer with strong expertise in ML Ops, cloud development, and production deployment. The ideal candidate will play a key role in transforming data science solutions into scalable, reliable, and production-ready machine learning systems.
Key Responsibilities
Convert data science Proof-of-Concept solutions into production-grade, automated pipelines hosted on Databricks (Cloud).
Implement CI/CD pipelines , model deployment automation, and ML Ops best practices.
Build scalable data and model pipelines ensuring reliability, performance, and observability.
Monitor model and pipeline performance, implement alerting, and handle issue remediation.
Maintain and enhance existing production tools and ML workloads.
Ensure alignment with Enterprise AI standards , architecture guidelines, and security requirements.
Collaborate with Data Scientists and platform teams for seamless migration and long-term sustainment.
Required Skills & Experience
Strong experience in ML Ops, cloud-based ML deployment, and automation
Hands-on experience with Databricks , CI/CD, and pipeline orchestration
Expertise in Python, ML frameworks, and production-grade systems
Strong understanding of model monitoring, governance, and security
Excellent collaboration and problem-solving skills
How to Apply
If you are interested in this opportunity, kindly share your updated resume with:
We’re Hiring: Machine Learning Engineer (ML Ops / Production Cloud Development & Sustainment)
Company: SRS Infoway
Job Position: Machine Learning Engineer – ML Ops / Production Cloud
Work Mode: Hybrid
Job Location: Bengaluru, Karnataka, India
SRS Infoway is looking for an experienced Machine Learning Engineer with strong expertise in ML Ops, cloud development, and production deployment. The ideal candidate will play a key role in transforming data science solutions into scalable, reliable, and production-ready machine learning systems.
Key Responsibilities
Convert data science Proof-of-Concept solutions into production-grade, automated pipelines hosted on Databricks (Cloud).
Implement CI/CD pipelines , model deployment automation, and ML Ops best practices.
Build scalable data and model pipelines ensuring reliability, performance, and observability.
Monitor model and pipeline performance, implement alerting, and handle issue remediation.
Maintain and enhance existing production tools and ML workloads.
Ensure alignment with Enterprise AI standards , architecture guidelines, and security requirements.
Collaborate with Data Scientists and platform teams for seamless migration and long-term sustainment.
Required Skills & Experience
Strong experience in ML Ops, cloud-based ML deployment, and automation
Hands-on experience with Databricks , CI/CD, and pipeline orchestration
Expertise in Python, ML frameworks, and production-grade systems
Strong understanding of model monitoring, governance, and security
Excellent collaboration and problem-solving skills
How to Apply
If you are interested in this opportunity, kindly share your updated resume with:
Apply for this Position
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