Machine Learning Operations 3 - 8 Yrs

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