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Alignity Solutions

Machine Learning Operations 3 - 8 Yrs

Seri Lingampally, INPresencialPermanenteTiempo completo

Publicado 30 sept 2026

Este empleo está publicado en EN

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.
  • Jobseeker Video Testimonials
  • Employee Glassdoor Reviews
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
  • 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

Visit us at http://alignity.io/careers. Alignity Solutions is an Equal Opportunity Employer, M/F/V/D.

CEO Message: Click Here
Clients Testimonial: Click Here

Resumen del puesto

Tipo de empleo

Tiempo completo

Habilidades requeridas

MLOpsModel Training & EvaluationFeature EngineeringModel Retraining StrategiesModel Monitoring and Performance EvaluationAWS SageMaker Unified StudioDesigning and Building Scalable ML PipelinesModel Lifecycle ManagementCore ML Frameworks (e.g., TensorFlow, PyTorch)AWS Infrastructure (strong understanding)AWS ML/AI Services (experience with related services)TerraformTroubleshooting and Problem-SolvingAbility to Work Independently in Project Environments

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