Google Cloud GenAI Developer

$63,200 - $169,800/Yr

Accenture - Boston, MA

Full-time - Senior

Boston, MA

Professional, Scientific, and Technical Services

About the position

The Generative AI Developer at Accenture is responsible for designing, implementing, and managing advanced Generative AI solutions on the Google Cloud Platform (GCP). This role involves collaborating with various teams to understand client needs and translating them into effective AI solutions, leveraging a deep understanding of Generative AI models and MLOps principles. The position offers an opportunity to work on innovative projects that address complex business challenges, while fostering a culture of inclusivity and diversity.

Responsibilities

• Develop and implement Generative AI solutions, collaborating with cross-functional teams.
• Support the successful execution of AI projects for a diverse range of clients.
• Conduct model tuning and optimization to improve model accuracy, efficiency, and robustness.
• Demonstrate deep knowledge of ML frameworks such as TensorFlow, PyTorch, Keras, Spacy, and scikit-learn.
• Develop and optimize search models, pipelines, and workflows for efficient data retrieval and relevance ranking.
• Utilize Google Vertex AI AutoML capabilities to build custom search models for specific use cases.
• Integrate VertexAI search functionalities into existing applications and systems.
• Implement best practices for data indexing, query optimization, and performance tuning within the Google Vertex AI framework.
• Monitor, analyze, and optimize data platform performance to ensure optimal efficiency and cost-effectiveness.
• Stay updated on the latest GCP data technologies, evaluating and recommending their adoption within the organization.
• Develop clear and comprehensive documentation, including architectural diagrams, design specifications, and operational guidelines.

Requirements

• Minimum 3 years of experience designing and deploying with one or more ML frameworks: TensorFlow, PyTorch, JAX, Spark ML, etc.
• Minimum 3 years of experience training and fine-tuning models in large-scale environments (e.g., image, language, recommendation) with accelerators.
• Minimum 2 years experience with distributed training and optimizing performance versus costs.
• Minimum 2 years of experience with CI/CD solutions in the context of MLOps and LLMOps including automation with IaC (e.g., using terraform).
• Minimum 2 years experience in systems design with the ability to design and explain data pipelines, ML pipelines, and ML training and serving approaches.
• Minimum 3 years of experience working with RAG technologies and LLM frameworks, LLM model registries (VertexAI Model Garden, Hugging Face), LLM APIs, embedding models, and vector databases.
• Bachelor's degree or equivalent (minimum 12 years) work experience.

Nice-to-haves

• Experience with Generative AI Studio for prototyping and experimenting with generative AI models.
• Familiarity with Google's Model Garden and its offerings for accessing and deploying pre-trained GenAI models.
• Experience in implementing MLOps practices for the development, deployment, and monitoring of GenAI models.
• Proven track record in designing and implementing cloud-based data architectures.
• Excellent analytical and problem-solving skills.
• Strong communication and interpersonal skills, capable of collaborating effectively with various teams.
• GCP Machine Learning Engineer or equivalent certifications are highly desirable.

Benefits

• Diversity and inclusion programs
• Professional development opportunities
• Flexible work arrangements
• Health and wellness programs