Machine Learning Engineer at Entain

Hyderabad, Telangana, India -

Full Time

Start Date

Immediate

Expiry Date

27 May, 26

Salary

0.0

Posted On

26 Feb, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, MLOps, Cloud-Native ML Tooling, AWS, GCP, Docker, Airflow, Prefect, CI/CD, GitLab CI, GitHub Actions, Jenkins, Terraform, CloudFormation, Model Governance, Feature Stores

Industry

Entertainment Providers

Description

Company Description Entain India is the engineering and delivery powerhouse for Entain, one of the world’s leading global sports and gaming groups. Established in Hyderabad in 2001, we’ve grown from a small tech hub into a dynamic force, delivering cutting-edge software solutions and support services that power billions of transactions for millions of users worldwide. Our focus on quality at scale drives us to create innovative technology that supports Entain’s mission to lead the change in global sports and gaming sector. At Entain India, we make the impossible possible, together. Job Description About the Role We are looking for a hands-on, cloud-savvy Machine Learning Engineer with 2+ years of experience to join our Data Science & AI Center of Excellence (CoE). In this role, you will help design, operationalize, and scale production-grade machine learning systems that power real-time, high-availability betting and gaming experiences. You will work closely with Data Scientists, ML Engineers, Cloud Engineers, and Product teams to build end-to-end ML pipelines, automate deployment workflows, and ensure models run efficiently, reliably, and securely in production environments. This position is ideal for someone who is passionate about MLOps, automation, cloud-native ML tooling, and scalable model governance. Key Responsibilities MLOps & Productionization Build and maintain automated ML pipelines for training, testing, deployment, and monitoring of models. Deploy ML models to production using modern MLOps frameworks, CI/CD pipelines, containerization, and orchestration systems. Implement robust model versioning, lineage, reproducibility, and governance practices. Model Monitoring & Reliability Develop monitoring dashboards and alerts for model performance, data drift, feature quality, and service health. Ensure uptime, scalability, and resilience of ML services in real-time, high-traffic environments. Data Engineering & Feature Delivery Collaborate with Data Engineering to build high-quality feature pipelines, implement feature stores, and optimize data flows for training and inference. Build data validation checks, data quality alerts, and schema enforcement. Cloud & Infrastructure Design cloud-native ML workflows using AWS/GCP services (depending on company stack). Optimize resource usage, cost efficiency, and infrastructure automation for ML workloads. Collaboration & Best Practices Work with the CoE team to establish MLOps best practices, templates, reusable components, and internal frameworks. Partner with Data Science teams to accelerate model development lifecycle while ensuring compliance and security. Contribute to technical documentation, design reviews, and knowledge-sharing initiatives. Qualifications Technical Experience 2+ years of hands-on experience in Machine Learning Engineering or MLOps roles. Strong proficiency in Python and ML/DS libraries (e.g., scikit-learn, pandas, NumPy). Experience building and deploying ML models into production. Practical experience with containerization (Docker) and orchestration (e.g., airflow, prefect, etc). Experience with CI/CD pipelines (GitLab CI, GitHub Actions, Jenkins, etc.). Understanding of ML lifecycle management: experiment tracking, feature engineering, model validation, monitoring, retraining. Cloud & DevOps Hands-on experience with cloud platforms (AWS, GCP) and ML-native cloud services. Familiarity with infrastructure-as-code tools (Terraform, CloudFormation, etc.). Soft Skills Strong problem-solving abilities and ownership mindset. Ability to work in a fast-paced, highly collaborative environment. Clear communication skills with both technical and non-technical stakeholders. Additional Information We know that signing top players requires a great starting package, and plenty of support to inspire peak performance. Join us, and a competitive salary is just the beginning. Depending on your role and location, you can expect to receive benefits like: Safe home pickup and home drop (Hyderabad Office Only) Group Mediclaim policy Group Critical Illness policy Communication & Relocation allowance Annual Health check And outside of this, you’ll have the chance to turn recognition from leaders and colleagues into amazing prizes. Join a winning team of talented people and be a part of an inclusive and supporting community where everyone is celebrated for being themselves. At Entain India, we do what’s right. It’s one of our core values and that’s why we're taking the lead when it comes to creating a diverse, equitable and inclusive future - for our people, and the wider global sports betting and gaming sector. However you identify, across any protected characteristic, our ambition is to ensure our people across the globe feel valued, respected and their individuality celebrated. We comply with all applicable recruitment regulations and employment laws in the jurisdictions where we operate, ensuring ethical and compliant hiring practices globally. Should you need any adjustments or accommodations to the recruitment process, at either application or interview, please contact us. Advertising Department: Technology Referral Band: ♥

Responsibilities

The role involves building and maintaining automated ML pipelines for training, testing, deployment, and monitoring of models, while ensuring models run efficiently, reliably, and securely in production environments. Key tasks include deploying ML models using modern MLOps frameworks and developing monitoring dashboards for model performance and service health.