Genpact Hiring Fresher Software Engineer – MLOps

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Genpact  a global professional services and solutions firm delivering outcomes that shape the future. Our 125,000+ people across 30+ countries are driven by our innate curiosity, entrepreneurial agility, and desire to create lasting value for clients.

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Genpact inviting applications for the role of Software Engineer – MLOps.

Job Designation : Software Engineer – MLOps

Qualification : BE/BTech/MCA

Experience : Freshers / experienced

Skill Set :

1. Strong programming skills in languages such as Python, Java, or Scala.
2. Experience with cloud platforms such as AWS, Azure, or GCP.
3. Proficiency in containerization technologies like Docker and Kubernetes.
4. Knowledge of machine learning concepts and frameworks (e.g., TensorFlow, PyTorch).
5. Experience with CI/CD tools (e.g., Jenkins, GitLab CI) and infrastructure-as-code (e.g., Terraform).
6. Excellent problem-solving and analytical skills.
7. Strong communication and collaboration abilities.

Job Description :

 

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Software Engineer – MLOps is responsible to design and architect scalable solutions that leverage ML algorithms, deep learning models and other AI techniques. This role must navigate successfully between the stakeholder groups, data scientists and ML Engineers and deliver & deploy AI models and applications, work with the team to promote the Gen AI/AI capabilities & services. 

Infrastructure Design and Implementation: 

1. Design and build scalable infrastructure for deploying and managing machine learning models in production environments.
2. Implement CI/CD pipelines to automate model deployment and updates.

Automation and Optimization: 

1. Develop automation scripts and tools to streamline the ML pipeline, improving efficiency and reducing manual intervention.
2. Optimize models for performance, scalability, and cost-effectiveness.

Collaboration and Support: 

1. Collaborate with cross-functional teams to understand model requirements and provide infrastructure support.
2. Work closely with data scientists and software engineers to ensure smooth integration of ML models into production systems.

Monitoring and Maintenance: 

1. Implement monitoring and alerting systems to track the performance and health of deployed models.
2. Troubleshoot issues and perform root cause analysis to ensure the reliability and availability of ML systems.

Security and Compliance: 

1. Ensure the security and compliance of ML systems, including data privacy and protection measures.
2. Stay informed about industry best practices and standards in ML Ops security.

Documentation and Training: 

1. Document infrastructure, processes, and procedures to facilitate knowledge sharing and ensure reproducibility.
2. Provide training and support to stakeholders on ML Ops best practices and tools.

Location : Hyderabad, Telangana, India