Artificial Intelligence Engineer - Python

Position : AI Engineer (Python + Generative AI)

Experience : 7 - 11 years

Location : Work From Home

Job Summary :

We are seeking a highly skilled and experienced AI Engineer with a strong background in Python and Generative AI. The ideal candidate will be an expert in the end-to-end development of AI systems, from prototyping and model training to deployment and optimization. This role requires a hands-on engineer who can design and build robust, scalable applications using Large Language Models (LLMs) and other generative technologies to drive business innovation.

Key Responsibilities :

Generative AI Model Development & Engineering :

- Implement and fine-tune Large Language Models (LLMs) using techniques such as Retrieval-Augmented Generation (RAG) and prompt engineering.

- Develop and optimize data pipelines for ingesting, cleaning, and transforming large datasets to be used in model training.

System Design & Architecture :

- Integrate Generative AI models into enterprise systems using RESTful APIs, microservices, and event-driven architectures.

- Design and build robust data retrieval systems, including leveraging vector databases for semantic search.

MLOps & Deployment :

- Build and manage CI/CD pipelines for continuous integration and deployment of AI models and applications.

- Monitor model performance, latency, and resource utilization in production environments.

Research & Innovation :

- Conduct research and experimentation to evaluate new models, frameworks, and techniques for potential business applications.

Collaboration & Leadership :

- Provide technical leadership and mentorship to junior team members.

Required Skills :

Programming & Core Engineering :

- Strong background in software engineering, including object-oriented programming, data structures, and algorithms.

Generative AI & LLMs :

- Proven hands-on experience with LLMs, including fine-tuning and RAG.

- Deep understanding of deep learning frameworks such as PyTorch or TensorFlow.

MLOps & Cloud Platforms :

- Hands-on experience with MLOps tools (e.g., MLflow, Kubeflow) and containerization technologies (Docker).

Databases & APIs :

- Proficiency in SQL and experience with building and consuming RESTful APIs.

Libraries & Frameworks :

Preferred Skills :

- Knowledge of specific cloud AI services (AWS Bedrock, Azure OpenAI Service, GCP Vertex AI).

- Experience with real-time data streaming technologies such as Kafka.

- Relevant professional certifications in AI/ML or cloud computing.

- Contributions to open-source AI projects.