Data Scientist

Data Scientist

Location: Alpharetta, GA (Onsite)
Interview: MS team interview/In-person

Job Summary:

We are seeking a skilled and innovative Machine Learning Engineer / Data Scientist with expertise in Google Cloud Platform (Google Cloud Platform), Databricks, Kubernetes, and Generative AI. This role involves designing and deploying scalable ML solutions, integrating cutting-edge generative models, and establishing robust monitoring systems to ensure performance and reliability in production environments.

 Key Responsibilities:

• Design, develop, and deploy ML models and AI solutions using Google Cloud Platform and Databricks.
• Build scalable data pipelines and ML workflows using Spark, Delta Lake, and Google Cloud Platform services (BigQuery, Vertex AI, Cloud Functions).
• Containerize and orchestrate ML applications using Docker and Kubernetes.
• Integrate and fine-tune Generative AI models (e.g., LLMs, decoder models) for tasks such as summarization, content generation, and intelligent automation.
• Experience implementing RAG pipelines using Vertex AI, Google Cloud Platform’s AI Embeddings API, and vector search capabilities in Google Cloud’s Vertex AI Matching Engine to enable scalable semantic retrieval for LLM-based applications.
• Proficient in managing embedding generation and indexing workflows within Google Cloud Platform, including integration with BigQuery, Cloud Storage, and Vertex AI Feature Store to support real-time and batch retrieval for generative AI use cases.
• Establish end-to-end monitoring for ML systems in Google Cloud Platform using tools like Cloud Monitoring, Vertex AI Model Monitoring, and Cloud Logging like Define and track key performance metrics such as Model accuracy, precision, recall, F1-score etc.,
• Implement MLOps best practices using MLflow, Vertex AI Pipelines, and CI/CD frameworks.
• Ensure compliance with data governance, privacy, and security standards.

 

Required Qualifications:

• Bachelor’s or master’s degree in computer science, Data Science, Engineering, or related field.
• 5+ years of experience in ML/AI development and deployment.
• Strong programming skills in Python and ML libraries (scikit-learn, TensorFlow, PyTorch).
• Hands-on experience with Google Cloud Platform services and Databricks.
• Proficiency in Kubernetes and containerized ML deployment.
• Experience with Generative AI frameworks (e.g., Hugging Face, LangChain, OpenAI APIs).
• Familiarity with monitoring tools in Google Cloud Platform (Cloud Monitoring, Logging, Vertex AI).
• Strong understanding of distributed computing and big data processing.
• Experience with RESTful APIs and microservices architecture.