Associate Consultant

Key Responsibilities:

1. AI Solution Development:
   • Assist in the design and development of generative AI models and solutions for clients across various industries.
   • Work with senior engineers to implement AI models into business processes, ensuring the solutions align with client needs and objectives.
   • Participate in the creation of Proof of Concepts (PoCs) and Minimal Viable Products (MVPs) to demonstrate AI capabilities.
2. Client Project Delivery:
   • Support the delivery of AI solutions for client projects, ensuring timely execution and high-quality outcomes.
   • Collaborate with cross-functional teams to understand client requirements, translate them into technical specifications, and help drive the successful implementation of AI models.
   • Contribute to client presentations and demos, showcasing AI capabilities and how they address specific business challenges.
3. 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.
4. Data Management & Integration:
   • Work with data engineering teams to ensure smooth data collection, management, and integration for AI model development.
   • Help integrate AI models with existing data pipelines and systems, ensuring data is processed and utilized effectively for AI model training and deployment.
   • Ensure data quality and adhere to best practices for data governance and privacy when handling sensitive information.
5. Business Development & Practise Building
   • Work closely with business teams and clients to demonstrate the potential of AI and assess its feasibility for solving business challenges.
   • Lead feasibility studies, develop data strategies, support RFP responses, and demo to prospective clients.
6. 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.

Key Responsibilities:

1. AI Solution Development:
   • Assist in the design and development of generative AI models and solutions for clients across various industries.
   • Work with senior engineers to implement AI models into business processes, ensuring the solutions align with client needs and objectives.
   • Participate in the creation of Proof of Concepts (PoCs) and Minimal Viable Products (MVPs) to demonstrate AI capabilities.
2. Client Project Delivery:
   • Support the delivery of AI solutions for client projects, ensuring timely execution and high-quality outcomes.
   • Collaborate with cross-functional teams to understand client requirements, translate them into technical specifications, and help drive the successful implementation of AI models.
   • Contribute to client presentations and demos, showcasing AI capabilities and how they address specific business challenges.
3. 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.
4. Data Management & Integration:
   • Work with data engineering teams to ensure smooth data collection, management, and integration for AI model development.
   • Help integrate AI models with existing data pipelines and systems, ensuring data is processed and utilized effectively for AI model training and deployment.
   • Ensure data quality and adhere to best practices for data governance and privacy when handling sensitive information.
5. Business Development & Practise Building
   • Work closely with business teams and clients to demonstrate the potential of AI and assess its feasibility for solving business challenges.
   • Lead feasibility studies, develop data strategies, support RFP responses, and demo to prospective clients.
6. 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.

Qualifications & Experience:

• Educational Background:
  • BSc in Computer Science, Engineering, Statistics, or a related field.
  • Certifications or coursework in AI/ML or data engineering are a plus.

(Additionally, if you feel you are the right fit for the listed skills and can demonstrate why you would be a good fit for the role, we are open to all backgrounds that have demonstrated commitment and progression of your skillset through personal and professional engagements. We want to continue to build out our team with the best and brightest minds in the industry, and if you feel you can contribute to our strategic goals and our clients, we would love to hear from you)

• Work Experience:
  • 3+ years of experience in AI/ML, specifically in the development and deployment of generative AI models.
  • Hands-on experience working with Large Language Models (LLMs) like GPT, BERT, or similar technologies.
  • Familiarity with AI frameworks such as TensorFlow, PyTorch, and cloud platforms like Databricks and Snowflake.
• 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.