Core AI Engineer

01 Calix North America - Remote, OR

Full-time - Mid Level

Remote, OR

About the position

The Core AI Engineer position at Calix involves developing and deploying end-to-end Generative AI applications. This remote role focuses on creating advanced AI solutions, bridging research and production to address real-world problems. The engineer will collaborate with machine learning engineers, AI researchers, and data engineers to build scalable, high-performance AI systems, particularly in areas like Natural Language Processing (NLP) and predictive analysis.

Responsibilities

• Design and develop production software components.
• Develop efficient data ingestion, feature engineering, and data pipelines at production scale.
• Collaborate with data engineers to preprocess and manage large datasets, ensuring that data pipelines are efficient and optimized for model training.
• Automate collection and visualization of data, model, and operational metrics.
• Implement and manage MLOps pipelines to automate model deployment, monitoring, and maintenance.
• Deploy models in scalable production environments using cloud platforms like AWS, GCP, or Azure.
• Work with cross-functional teams, including software engineers and data scientists, to design system architectures that integrate AI models into existing or new platforms.
• Extend, harden, and scale data processing and ML components.
• Perform data ingestion, data processing, and feature engineering tasks.
• System integration to bring AI features to other applications and platforms.
• Build and deploy microservices for AI features.
• Operate and administer production databases: SQL, NoSQL, Vector, and Graph.
• Troubleshoot and support production pipeline.
• Work with ops team for end-to-end deployment of data and ML pipelines.

Requirements

• Bachelor's or Master's degree in Computer Science or a related field.
• 5+ years of hands-on experience in AI/ML engineering, building and deploying machine learning models in production environments.
• Proven track record in developing end-to-end AI applications across different domains, such as NLP, computer vision, or predictive modeling.
• Solid foundation in data structures and algorithms.
• Proficient in deep learning frameworks such as TensorFlow, PyTorch, or Keras.
• Proficiency in Python and one other language (Java, Go, C/C++, R, SQL).
• Experience with SQL, Pandas, and exposure to various SQL and NoSQL databases.
• Solid understanding of data engineering and experience working with large datasets and building ETL pipelines.
• Experience automating unit, system, and production testing.
• Experience in data processing: ETL, feature engineering, data cleaning.
• Proficiency in developing in Linux environments with git.
• Experience with cloud platforms (AWS, GCP, Azure) and deploying models in containerized environments using Docker and Kubernetes.
• Experience developing microservices and REST APIs.

Nice-to-haves

• Experience with multimodal AI systems (text, image, video).
• Knowledge of DevOps principles and CI/CD pipelines for automated testing and deployment.
• Familiarity with natural language understanding (NLU), automatic speech recognition (ASR), and dialog systems.
• Contributions to open-source AI projects or publications in AI/ML conferences and journals.
• Experience with GenAI: RAG pipeline components, LLM pre-training, alignment, fine-tuning, and different types of LLM and their applications.

Benefits

• Competitive salary based on geographical location.
• Comprehensive health insurance coverage.
• Flexible work hours and remote work options.
• Opportunities for professional development and learning.
• Paid time off and holidays.