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 : Google Cloud Platform (GCP)
Good to have skills : NA
Minimum
3 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary:
As an AI / ML Engineer, a typical day involves designing and building advanced applications and systems that leverage artificial intelligence tools and cloud-based services. The role requires integrating these solutions into robust pipelines that are ready for production environments, whether hosted on cloud platforms or on-premises. The engineer actively works on implementing generative artificial intelligence models and may engage with various technologies such as deep learning, neural networks, chatbots, and image processing to create innovative and efficient solutions that meet project requirements and business goals.
Roles & Responsibilities:
- Expected to perform independently and become an SME.
- Required active participation/contribution in team discussions.
- Contribute in providing solutions to work related problems.
- Collaborate with cross-functional teams to ensure seamless integration of AI models into existing systems.
- Continuously monitor and optimize deployed applications for performance and scalability.
- Assist junior team members by sharing knowledge and providing guidance on technical challenges.
- Stay updated with the latest advancements in AI and cloud technologies to recommend improvements.
- Key responsibilities
- Provision and manage compute (GCE, GKE, Cloud Run), storage (GCS, Cloud SQL), and networking (VPC, Load Balancers, DNS) on GCP.
- Codify infrastructure using Terraform and the gcloud SDK build and maintain CI/CD pipelines via Cloud Build, GitHub Actions, or Jenkins.
- Deploy containerized workloads on GKE and Cloud Run support AI service deployments including vector stores and model-serving endpoints.
- Operationalize monitoring, logging, and alerting through Cloud Logging, Cloud Monitoring, and Stackdriver.
- Apply cost-optimization and security best practices across IAM, VPC Service Controls, and KMS.
- Automate routine operations with Python or Bash collaborate with developers to troubleshoot production incidents.
Professional & Technical Skills:
- Must To Have Skills: Proficiency in Google Cloud Platform (GCP).
- Experience with cloud infrastructure management and deployment strategies.
- Strong understanding of AI and machine learning frameworks and their application in cloud environments.
- Ability to design and implement scalable AI pipelines that support production-grade solutions.
- Familiarity with generative AI models and their integration into business applications.
- Knowledge of containerization and orchestration tools to support cloud-native deployments.
- Must-have skills: GCP (GCE, GKE, Cloud Run, GCS, BigQuery, Pub/Sub, Cloud Functions, IAM, VPC), cloud infrastructure, Terraform, Docker / Kubernetes, Python / Bash scripting, CI/CD. GCP Associate Cloud Engineer certification preferred.
Additional Information:
- The candidate should have minimum 3 years of experience in Google Cloud Platform (GCP).
- This position is based at our Bengaluru office.
- A 15 years full time education is required.
- Experience: 3–5 years in cloud engineering with strong hands-on GCP experience.
