AI/ML Engineer
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The hb Club
Jan 13, 2026, 2:12:54 PM (8 days ago) Jan 13
to NewC2Creqs
Hi, PFB
AI/ML Engineer
ALPHARETTA, GA (Onsite)
Skills: AI/ML Engineering
ALPHARETTA, GA (Onsite)
Skills: AI/ML Engineering
11+ years Exp
Job Description:
We are seeking a skilled and innovative Machine Learning Engineer / Data Scientist with expertise in Google Cloud Platform (GCP), 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 GCP and Databricks.
Build scalable data pipelines and ML workflows using Spark, Delta Lake, and GCP 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, GCP’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 GCP, 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 GCP 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.
We are seeking a skilled and innovative Machine Learning Engineer / Data Scientist with expertise in Google Cloud Platform (GCP), 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 GCP and Databricks.
Build scalable data pipelines and ML workflows using Spark, Delta Lake, and GCP 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, GCP’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 GCP, 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 GCP 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.
Thanks and Regards,
Harsha Byreddy
Talent Acquisition Specialist
Stellarwins Solutions LLC
Email: hars...@stellarwins.com
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