AS
Alignity Solutions
Machine Learning Operations 3 - 8 Yrs
Seri Lingampally, INSur siteCDITemps plein
Publié 30 sept. 2026
Cet emploi est publié 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.
Role:Machine Learning Operations (MLOps) Engineer/Practitioner
Location: Hyderabad
Work Mode: Hybrid
Relevent Experience: 3-8 Years
Type: Contract to Hire
Job Summary
Key Responsibilities
Required Skills
Good to Have
Candidate Profile
CEO Message: Click Here
Clients Testimonial: Click Here
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
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.
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
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
Aperçu du poste
Type de poste
Temps plein
Compétences requises
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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