What are the responsibilities and job description for the Senior AI Engineer position at G-P?
As a Senior AI Engineer, you will design, develop, and deploy AI solutions that address complex business challenges. This role requires advanced expertise in artificial intelligence, including machine learning and natural language processing, and the ability to implement these technologies in production-grade systems.
Key Responsibilities:
- Develop innovative, scalable AI solutions for real business problems. Drive the full lifecycle of projects from conception to deployment, ensuring alignment with business objectives.
- Manage complex data sets, design efficient data processing pipelines, and train robust models. Expect to spend approximately 70% of your time on data and ML engineering tasks related to developing AI systems.
- Own highly open-ended projects end-to-end, from the analysis of business requirements to the deployment of solutions. Dedicate about 30% of your time to researching new techniques in NLP and ML that could benefit the business.
- Work closely with other AI engineers, product managers, and stakeholders to ensure that AI solutions meet business needs and enhance user satisfaction.
- Write clear, concise, and comprehensive technical documentation for all projects and systems developed.
- Stay updated on the latest developments in the field. Explore and prototype new technologies and approaches to address specific challenges faced by the business.
- Develop and maintain high-quality machine learning services. Prioritize robust engineering practices and user-centric development.
Required Skills and Qualifications:
- Master’s degree in Computer Science, Machine Learning, Statistics, Engineering, Mathematics, or a related field
- Deep understanding and practical experience in machine learning and natural language processing, especially with deep learning architectures
- Strong foundational knowledge in statistical modeling, probability, and linear algebra
- Extensive practical experience with curating datasets, training models, analyzing post-deployment data, and developing robust metrics to ensure model reliability
- Experience developing and maintaining machine learning services for real-world applications at scale
- Strong Python programming skills and ability to write maintainable, production-ready code
- Proficiency with Container Orchestration services such as Docker
- Proficiency with AWS, including Serverless
- Proven track record in driving AI projects with strong technical leadership.
- Excellent communication skills when engaging with both technical and non-technical stakeholders
- Proactive attitude with a continuous improvement mindset, seeking help and providing feedback when necessary
Preferred Qualifications:
- Experience with LLMs for non conversational use cases
- Experience with natural language processing for legal applications
- Proficiency with Terraform
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