DATA SCIENCE AND MACHINE LEARNING-GACOR805523

Onshore-Junior Developer
Work Location: DATA SCIENCE AND MACHINE LEARNING-GACOR805523
Location: Sandy Springs GA
Interview: Online

Work Mode: Hybrid

Job Description: Machine Learning Engineer MLOps VertexAI LLMs GenAI ML Model Management
We are seeking a highly skilled MLOps Engineer to design deploy and manage machine learning pipelines in Google Cloud Platform (GCP). In this role you will be responsible for automating ML workflows optimizing model deployment ensuring model reliability and implementing CI/CD pipelines for ML systems.

You will work with Vertex AI Kubernetes (GKE) BigQuery and Terraform to build scalable and cost-efficient ML infrastructure. The ideal candidate must have a good understanding of ML algorithms experience in model monitoring performance optimization Looker dashboards and infrastructure as code (IaC) ensuring ML models are production-ready reliable and continuously improving. You will be interacting with multiple technical teams including architects and business stakeholders to develop state of the art machine learning systems that create value for the business.

Under general supervision works on software development assignments within a specific software functional area or product line
Conducts unit testing on the module
Involved in execution and reporting for system integration testing and regression testing

Mandatory Skills:

Expertise in programming languages like Python SQL
Solid understanding of best MLOps practices and concepts for deploying enterprise-level ML systems
Understanding of Machine Learning concepts models and algorithms including traditional regression clustering models and neural networks (including deep learning transformers etc.)
Understanding of model evaluation metrics model monitoring tools and practices
Experienced with GCP tools like BigQueryML MLOps Vertex AI Pipelines (Kubeflow Pipelines on GCP) Model Versioning & Registry Cloud Monitoring Kubernetes etc.
Solid written and verbal communication skills and ability to prepare detailed technical documentation of new and existing applications
Strong ownership and collaborative qualities in their domain. Takes initiative to identify and drive opportunities for improvement and process streamlining
Bachelors Degree in a quantitative field of mathematics computer science physics economics engineering statistics (operations research quantitative social science etc.) international equivalent or equivalent job experience

Desired Skills:

Experience in Azure MLOPS
Familiarity with Cloud Billing
Experience in setting up or supporting NLP Gen AI LLM applications with MLOps features
Experience working in an Agile environment understanding of Lean Agile principles