Role & responsibilities:

1. Generative AI Solution Development:

- Develop and implement advanced solutions using Generative AI technologies, leveraging frameworks such as Python, LangChain, and HuggingFace.
- Engage in prompt engineering, working with Large Language Models (LLMs) to create tailored AI-driven solutions.
- Ensure response accuracy of prompts. Make sure the prompts generate desired outcomes and adhere to instructions.

2. Model Fine-Tuning and Optimization:

- Fine-tune pre-trained models from HuggingFace and other platforms to meet project-specific requirements.
- Optimize AI models for efficiency, accuracy, and scalability in educational contexts.
- Achieve minimum accuracy thresholds for models
- Reduce model training time and computational resource usage.
- Innovate AI techniques or algorithms at least once per quarter.

3. Collaboration with Business Teams:

- Collaborate with business stakeholders to align AI solutions with organizational goals, translating business requirements into technical specifications.
- Participate in cross-functional collaboration meetings, ensuring effective communication of AI model capabilities.

4. AI Frameworks and Tooling:

- Utilize frameworks like LangChain, Cohere, Keras, TensorFlow, and PyTorch for developing, testing, and deploying AI models.
- Integrate AI solutions into existing systems for seamless user experiences.
- Ensure AI deployment times are within defined timelines (e.g., from training to production).
- Maintain model latency below a defined threshold for real-time inference (e.g., under decided milliseconds).

5. Research and Innovation:

- Stay updated on the latest advancements in Generative AI, machine learning, and deep learning technologies.




- Experiment with new methodologies and emerging AI technologies to innovate and enhance existing solutions.
- Introduce innovative AI algorithms or approaches at least once per quarter.

6. System Architecture and Integration:

- Design robust system architectures using frameworks like FastAPI and Unicorn to support AI-driven applications.
- Ensure AI solutions are scalable, maintainable, and integrated effectively with other system components.
- Ensure efficient use of computing resources and optimize costs while maintaining performance standards.

7. Performance Monitoring and Improvement:

- Monitor AI model performance, applying ML engineering metrics to continuously improve outcomes.
- Troubleshoot issues related to model performance and integration, resolving critical bugs quickly.
- Reductions in code execution time and model bugs.
- Ensure AI-related code has unit testing coverage for robustness.

8. Documentation:

- Provide comprehensive documentation for all developed models, data pipelines, and processes, explaining functionality and edge cases.
- Maintain detailed documentation of current features and code implementations.
- Ensure step-by-step deployment and retraining documentation, with minimal user-reported gaps or confusion.

Preferred candidate profile:

- Education: Bachelor's degree or equivalent experience in Computer Science, AI, or related fields.
- Experience: 3-5 years of experience, with at least 1 year specializing in AI/ML.
- Key Skills: Prompt Engineering, Python Programming, AI and ML Frameworks, Deep Learning Architectures, Mathematical and Statistical Knowledge, System Architecture Design, Model Fine-Tuning, Collaboration and Communication, Continuous Learning.

📌 Artificial Intelligence Engineer (Maharashtra)
🏢 Aptech
📍 Maharashtra