Lead Generative AI Engineer

This role is for one of Weekday's clients
Min Experience: 8 years
Location: Bengaluru
JobType: full-time

Requirements

About the Role
As a Lead Gen AI Engineer in our Team, you'll work closely with the Automation Delivery Director, Architects, Technical Lead and delivery squads in Designing and Building world class AI solutions within Automation Centre. You will be responsible for Solution Design, Development, Testing and deployment of AI initiatives by partnering with Operations,
Technology and Vendor partners.

Responsibilities:

1. System Design and Architecture: Design optimised architectures for Gen AI and agent-based solutions at scale
2. Develop and Integrate AI Models: Design, implement, and deploy generative AI models and Machine Learning solutions to meet specific business needs.
3. Web API Development: Build, maintain, and document RESTful and GraphQL APIs for seamless integration of AI services with web and mobile applications using fastapi, Flask, etc
4. Model Deployment and Monitoring: Implement, deploy, and monitor ML models on cloud platforms or on-premise environments using frameworks like TensorFlow, PyTorch, or Hugging Face. Experienced in Kubernetes
5. Data Processing and Management: Preprocess large datasets, manage data pipelines, and optimize data storage for AI/ML applications.
6. Collaborate with Cross-functional Teams: Work closely with data scientists, software engineers, and product managers to design scalable solutions and deploy AI-driven features.
7. Optimize Code for Performance: Write clean, maintainable, and efficient Python code with an emphasis on scalability and performance.
8. Research and Experimentation: Stay up-to-date with the latest trends in Generative AI, LLMs, and ML, and proactively experiment with new technologies to improve current processes.
9. Mentorship and Leadership: Mentor junior engineers and provide guidance on best practices in AI/ML development.

Must Haves:

Education: Bachelor's degree in computer science, Engineering, Mathematics, or a
related field. A master's degree is a plus.

Experience:

1. 8+ years of professional experience
2. 6+ years of Python experience
3. Proven experience with productionising Generative AI based solutions
4. Proven experience with Machine Learning frameworks like TensorFlow, PyTorch, or Hugging Face.
5. Experience with Web APIs: RESTful API design, FastAPI, Flask/Django, and best practices for security and scalability.
6. Cloud Platforms: Familiarity with AWS, GCP, or Azure for deploying and scaling ML models.
7. Experience in Docker and containerised platforms
8. Experience in RAG and finetuning of foundational models
   

Skills

1. Python: Advanced proficiency in Python, with a strong understanding of libraries such as NumPy, Pandas, and Scikit-Learn.
2. ML/AI Tools: Hands-on experience with popular machine learning and deep learning frameworks like TensorFlow, PyTorch, and Keras.
3. Generative AI: Solid understanding of generative model concepts like (e.g., GPT, GANs, VAEs, and transformers). Knowledge of text and image generation models, fine-tuning, and prompt engineering.
4. Experience in langchain.
5. API Development: Skilled in designing, developing, and consuming APIs for real-time data processing and integration with other services.
6. Data Engineering: Proficiency in data preprocessing, feature engineering, and working with large datasets.
7. Deployment: Experience with Docker, Kubernetes, or serverless architectures for model deployment and scalability.
   Version Control: Git, GitHub, or Bitbucket.