Generative AI Engineer
Posted 4 days ago by PSD Technology Contracts Ltd.
£750 Per day
Inside
Hybrid
Hybrid Working , UK
Summary: The Generative AI Engineer role involves developing and deploying generative AI models and solutions within an advisory business. The position requires collaboration with senior AI professionals to drive impactful AI initiatives and ensure alignment with business objectives. The engineer will also focus on coding, implementation, and compliance with data governance policies. This is a hybrid working position for a duration of 6 months or more.
Key Responsibilities:
- Assist in the design and development of generative AI models and solutions across various Watts projects.
- Work with senior engineers to implement AI models into business processes, ensuring the solutions align with the businesses' needs and objectives.
- Write, optimize, and implement AI code for model development, integrating generative AI models into scalable production environments.
- Use tools such as TensorFlow, PyTorch, and cloud platforms like Databricks and Snowflake to build and deploy AI solutions.
- Collaborate with other engineers on coding best practices, version control, and continuous integration/continuous delivery (CI/CD) processes.
- Ensure compliance with KPMG's data governance policies and industry regulations regarding AI models and data processing.
- Implement best practices in data privacy, security, and ethical AI, particularly when handling sensitive data.
Key Skills:
- Proficient in coding and optimizing generative AI models, particularly in the areas of prompt engineering and LLMs.
- Familiarity with AI/ML algorithms and model deployment in cloud environments.
- Experience with version control tools (e.g., Git), and knowledge of Docker and containerization.
- Strong communication and collaboration skills, with the ability to work effectively in cross-functional teams.
- BSc in Computer Science, Statistics, Engineering, or related field.
- Advanced certifications in AI/ML, cloud computing, or data engineering are advantageous.
Salary (Rate): £750 per day
City: undetermined
Country: UK
Working Arrangements: hybrid
IR35 Status: inside IR35
Seniority Level: undetermined
Industry: IT
Role: Generative AI Engineer
Location: Hybrid Working
Rate: Up to £750 per day (Inside IR35) dep on exp
Length: 6 months+
Consultant: Thomas Peters, email (see below)
Our client, an advisory business, is seeking an experienced Generative AI Engineer (Tech Squad Member) to support the industrialisation of the tools developed during the programme.
In this role, you will be involved in the development and deployment of generative AI models and solutions, supporting key projects, and driving impactful AI initiatives. You'll work closely with senior AI professionals and contribute to designing and implementing AI solutions that deliver real business value.
AI Solution Development:
- Assist in the design and development of generative AI models and solutions across various Watts projects.
- Work with senior engineers to implement AI models into business processes, ensuring the solutions align the businesses' needs and objectives.
Coding & Implementation:
- Write, optimize, and implement AI code for model development, integrating generative AI models into scalable production environments.
- Use tools such as TensorFlow, PyTorch, and cloud platforms like Databricks and Snowflake to build and deploy AI solutions.
- Collaborate with other engineers on coding best practices, version control, and continuous integration/continuous delivery (CI/CD) processes.
Data Governance & Security
- Ensure compliance with KPMG's data governance policies and industry regulations regarding AI models and data processing.
- Implement best practices in data privacy, security, and ethical AI, particularly when handling sensitive data.
Skills:
- Proficient in coding and optimizing generative AI models, particularly in the areas of prompt engineering and LLMs.
- Familiarity with AI/ML algorithms and model deployment in cloud environments.
- Experience with version control tools (eg, Git), and knowledge of Docker and containerization.
- Strong communication and collaboration skills, with the ability to work effectively in cross functional teams.
Educational Background:
- BSc in Computer Science, Statistics, Engineering, or related field
- Advanced certifications in AI/ML, cloud computing, or data engineering are advantageous.