Role Overview:

We are looking for an experienced Senior Associate GCP AI to design, develop, deploy, and optimize AI/ML solutions on the Google Cloud Platform (GCP). The role involves building production-grade machine learning solutions, leveraging GCP AI services, supporting MLOps, and collaborating with data science and engineering teams.

Key Responsibilities:

- Design and implement scalable AI/ML solutions on Google Cloud Platform.

- Develop, train, deploy, and manage machine learning models using Vertex AI and related GCP services.

- Build and optimize ML solutions using frameworks such as TensorFlow, PyTorch, Keras, and scikit-learn.

- Develop data preprocessing, feature engineering, model training, validation, and inference pipelines.

- Integrate AI/ML models with enterprise applications, APIs, and existing data platforms.

- Use GCP AI capabilities such as Vertex AI, Vision AI, and Natural Language AI.

- Implement and support MLOps practices covering model versioning, deployment, monitoring, and lifecycle management.

- Optimize model performance, inference efficiency, scalability, and GCP resource utilization.

- Work with data engineers and data scientists to operationalize machine learning solutions.

- Leverage BigQuery, Dataflow, and other GCP data services.

- Monitor deployed models and troubleshoot performance, reliability, and production issues.

- Contribute to solution design, technical discussions, code reviews, and engineering best practices.

- Provide technical guidance and mentorship to junior team members.

- Collaborate with architects, data scientists, and clients to translate business requirements into scalable AI solutions.

- Stay current with developments in GCP AI services, Generative AI, and MLOps.

Required Skills:

- 6 - 7 years of experience in AI/ML engineering or machine learning development.

- Strong hands-on experience with Google Cloud Platform and Vertex AI.

- Strong proficiency in Python and AI/ML libraries such as TensorFlow, PyTorch, Keras, and scikit-learn.

- Strong understanding of machine learning algorithms, data preprocessing, feature engineering, and model evaluation.

- Experience developing and deploying machine learning models in production environments.

- Hands-on experience with MLOps and ML model lifecycle management.

- Experience with GCP data services such as BigQuery and Dataflow.

- Good understanding of cloud-based AI architecture, APIs, model serving, and scalability.

- Experience with AI services such as Vision AI and Natural Language AI is preferred.

- Strong troubleshooting, analytical, and problem-solving skills.

- Good understanding of software engineering practices including Git, testing, CI/CD, and deployment.

- Strong communication and stakeholder management skills.

- Ability to work effectively in cross-functional teams.

Good to Have :

- Google Cloud Professional Machine Learning Engineer certification.

- Experience with Generative AI, LLMs, or Vertex AI Generative AI capabilities.

- Exposure to AWS or Azure AI/ML platforms.

- Experience with Docker, Kubernetes, or containerized ML workloads.

- Prior experience in a client-facing consulting or technology services environment.

- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, Mathematics, or Statistics.