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The company is looking to develop and deploy scalable machine learning solutions to drive growth and transform data into impactful insights.

Requirements

• Python and Java programming languages
• ML Frameworks: TensorFlow, PyTorch, Scikit-learn
• Databases: BigQuery, PostgreSQL, Redis, MongoDB
• Cloud & DevOps: Kubernetes, Docker, Terraform, GCP, AWS
• MLOps Tools: MLflow, Kubeflow, Airflow
• AI Tools: GitHub Copilot, Cursor AI, Otter AI, ChatGPT
• NLP & LLMs: GPT, BERT, Transformer architectures

Responsibilities

• Design, develop, and deploy end-to-end machine learning systems optimized for performance, scalability, and rapid deployment
• Build and optimize data pipelines for efficient ingestion, transformation, and analysis
• Implement and fine-tune large language models (LLMs) like GPT, BERT, and integrate them seamlessly into production systems
• Design, develop, and implement CI/CD pipelines for continuous deployment and monitoring of machine learning models
• Build and maintain cloud-native ML applications on platforms like GCP, AWS, or Azure
• Rapidly prototype and deploy ML models and full-stack applications using AI-assisted development tools
• Tackle technical challenges, from optimizing algorithms to deploying real-time machine learning systems

Other

• Bachelor’s degree in Computer Science, Engineering, or equivalent hands-on experience
• 5+ years of hands-on experience in machine learning and full stack development
• Strong communication and collaboration abilities
• Ability to quickly understand and implement complex data models and algorithms
• Must be able to demonstrate lawful ability to work in the United States
• Must be located in the Bay Area, CA; Charlotte, NC; Denver, Colorado; and Atlanta, Georgia unless listed otherwise