Artificial Intelligence Engineer

Aptech Limited; Mumbai Suburban, Mumbai; On-site; INR 1,500,000 - 2,800,000; Full time

Job summary

Aptech Limited is seeking a hands-on AI engineer to build generative AI solutions, leveraging Python, LangChain, and popular ML frameworks. The role emphasizes prompt engineering, model fine-tuning, and delivering scalable educational AI applications.

You will collaborate with business teams to translate requirements into technical specs, design robust architectures with FastAPI, and monitor model performance to ensure low latency and high accuracy.

Qualifications

• Bachelor's degree in CS/AI or equivalent experience.
• 3–5 years of experience, with at least 1 year in AI/ML.
• Strong skills in prompt engineering and ML frameworks.

Responsibilities

• Develop generative AI solutions using Python, LangChain, and HuggingFace.
• Engineer prompts and ensure prompts yield desired outcomes.
• Fine-tune models from HuggingFace to meet project needs.
• Optimize models for efficiency, accuracy, and scalability.
• Collaborate with business teams to translate requirements.
• Design robust architectures with FastAPI and deployment readiness.
• Monitor model performance and reduce latency.
• Document models, pipelines, and deployment steps.

Skills

Prompt Engineering

Python Programming

AI Frameworks

Deep Learning

Model Fine-Tuning

System Architecture

ML Engineering

Collaboration & Communication

Continuous Learning

Education

Bachelor's degree in CS/AI or equivalent

Tools

LangChain

Cohere

Keras

TensorFlow

PyTorch

Job description

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 new 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.