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Machine Learning Operations 3 8 Yrs
Job Location:
Salary:
Experience Required:
Posted:
1 October 2026 (2 days ago)
Posted:
Application Deadline:
29 December 2026
Application Deadline:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
Do you love a career where you Experience Grow & Contribute at the same time while earning at least 10% above the market If so we are excited to have bumped onto you.
Learn how we are redefining the meaning of work and be a part of the team raved by Clients Job-seekers and Employees.
If you are a Machine Learning Operations (MLOps) Engineer looking for excitement challenge and stability in your work then you would be glad to come across this page.
We are an IT Solutions Integrator/Consulting Firm helping our clients hire the right professional for an exciting long-term project. Here are a few details.
Check if you are up for maximizing your earning/growth potential leveraging our Disruptive Talent Solution.
Role:Machine Learning Operations (MLOps) Engineer/Practitioner
Location: Hyderabad
Work Mode: Hybrid
Relevent Experience: 3-8 Years
Type: Contract to Hire
Requirements
Job Summary
We are looking for an experienced MLOps Practitioner to join our Canada Post project. The ideal candidate should have strong hands-on experience in machine learning operations model lifecycle management and AWS-based ML platforms.
Key Responsibilities
- Design and implement MLOps processes for machine learning model development and deployment.
- Work on model training evaluation retraining and monitoring.
- Perform feature engineering and support end-to-end ML workflows.
- Work with core Machine Learning frameworks and tools.
- Build and maintain scalable ML pipelines and model lifecycle processes.
- Utilize AWS SageMaker Unified Studio for ML development and operational workflows.
- Monitor model performance and implement model retraining strategies when required.
Required Skills
- Strong hands-on experience in MLOps.
- Experience with:
- Model Training & Evaluation
- Feature Engineering
- Model Retraining
- Model Monitoring
- Core ML Frameworks
- Model Training & Evaluation
- Strong experience with AWS SageMaker Unified Studio.
Good to Have
- Experience with Terraform.
- Strong understanding of AWS Infrastructure.
- Experience with AWS services related to ML/AI workloads.
- Knowledge of cloud-based MLOps architecture and best practices.
Candidate Profile
- Strong MLOps hands-on experience with an understanding of the complete ML lifecycle.
- Ability to work independently in a project environment.
- Strong troubleshooting and problem-solving skills.
- L35-level candidates are preferred.
Interested candidates can apply with their updated resume mentioning relevant MLOps and AWS SageMaker experience.
Benefits
CEO Message: Click Here
Clients Testimonial: Click Here
Required Skills:
Required skills: MLOps including model training evaluation feature engineering core ML frameworks model retraining and monitoring AWS SageMaker Unified Studio Good to have: Terraform AWS infrastructure experience
