Project Role : AI / ML Engineer
Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing.
Must have skills : Machine Learning Operations
Good to have skills : NA
Minimum
7.5 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary:
As an ML DevOps Architect, you will engage in the development of applications and systems that leverage artificial intelligence tools and cloud AI services. Your typical day will involve creating production-ready quality pipelines, applying generative AI models, and exploring various advanced technologies such as deep learning, neural networks, chatbots, and image processing. You will collaborate with cross-functional teams to ensure the successful implementation of AI solutions that meet business needs and enhance operational efficiency.
Must Have : Hands-on experience on CI/CD & Continuous Testing, Experience with PromptOps including logging, testing, monitoring, and prompt versioning. Strong cloud architecture experience with Azure Cloud and its services,Hands-on experience with Kubernetes, Docker, and Helm for container orchestration, Experience with Infrastructure as Code using Terraform (preferred) or ARM templates, Monitoring and logging (Native Azure monitoring tools, Prometheus, Grafana)
Experience with GitLab CI/CD pipelines for infrastructure and application (frontend/backend) deployment, Experience implementing DevSecOps practices
Roles & Responsibilities:
- Expected to be an SME, collaborate and manage the team to perform.
- Responsible for team decisions.
- Engage with multiple teams and contribute on key decisions.
- Provide solutions to problems for their immediate team and across multiple teams.
- Facilitate knowledge sharing and mentorship within the team to foster professional growth.
- Evaluate and implement new technologies and methodologies to improve project outcomes.
Professional & Technical Skills:
- Must To Have Skills: Proficiency in Machine Learning Operations.
- Good To Have Skills: Experience with cloud platforms such as AWS, Azure, or Google Cloud.
- Strong understanding of model deployment and monitoring techniques.
- Experience with containerization technologies like Docker and Kubernetes.
- Familiarity with programming languages such as Python or R for data analysis and model development.
Additional Information:
- The candidate should have minimum 7.5 years of experience in Machine Learning Operations.
- This position is based at our Pune office.
- A 15 years full time education is required.
