Job Summary:

We are seeking a highly skilled AI/ML Engineer with expertise in Microsoft Azure and experience in large language models (LLMs), and integrations with frameworks like PyTorch to join our team. The role demands familiarity with concepts of retrieval augmentation generation (RAG) and fine-tuning LLMs using techniques like Sparse Fine-Tuning (SFT) or Dense Passage Retrieval (DPO). The ideal candidate will have 2-3 years of experience in the field of artificial intelligence and machine learning, with a strong background in utilizing Microsoft Azure’s suite of tools and services for AI development. The candidate should possess excellent problem-solving abilities, be proficient in programming languages commonly used in AI development, and have a solid understanding of cloud computing principles.

Key Responsibilities:

1. Develop and deploy machine learning models using Microsoft Azure’s AI and ML services.
2. Collaborate with cross-functional teams to understand project requirements and translate them into technical solutions.
3. Design and implement scalable and efficient AI solutions leveraging Azure’s platform capabilities.
4. Optimize and fine-tune machine learning models for performance and accuracy.
5. Utilize Azure’s data storage and processing services for managing large datasets.
6. Implement automated pipelines for data ingestion, processing, and model deployment.
7. Conduct testing and validation of AI models to ensure reliability and robustness.
8. Stay updated on the latest advancements in AI technologies and Azure services.
9. Provide technical guidance and support to junior team members as needed.
10. Document code, processes, and best practices to facilitate knowledge sharing and collaboration within the team.

Qualifications:

1. Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
2. 2-3 years of professional experience in artificial intelligence and machine learning.
3. Strong proficiency in programming languages such as Python, R, or Java.
4. Experience with Microsoft Azure’s AI and ML services, including Azure Machine Learning, Azure Cognitive Services, and Azure Databricks.
5. Familiarity with large language models (LLMs), and integrations with frameworks like TensorFlow, PyTorch, scikit-learn, etc.
6. Familiarity with retrieval augmentation generation (RAG) and fine-tuning LLMs using techniques like Sparse Fine-Tuning (SFT) or Dense Passage Retrieval (DPO) will be a plus.
7. Knowledge of cloud computing concepts and experience with Azure cloud platform.
8. Experience with data preprocessing, feature engineering, and model evaluation techniques.
9. Excellent problem-solving skills and ability to work effectively in a team environment.
10. Strong communication skills with the ability to articulate complex technical concepts to non-technical stakeholders.
11. Demonstrated ability to manage multiple tasks and priorities in a fast-paced environment.