Senior AI Engineer

Job Summary
We are seeking a skilled AI/ML Engineer to design, develop, and deploy scalable artificial intelligence and machine learning solutions. This role focuses on leveraging both conventional ML models and cutting-edge Generative AI technologies, including large language models (LLMs) and text-to-SQL frameworks. The ideal candidate will manage the full ML lifecycle, optimize model performance, and integrate advanced AI services within cloud environments to deliver impactful AI-driven products.

Key Responsibilities
Design and develop scalable AI and ML solutions using a combination of traditional machine learning methods and Generative AI models. You will be responsible for building, fine-tuning, and deploying Generative AI applications in production, with a focus on large language models and text-to-SQL systems.

Manage the end-to-end machine learning lifecycle, encompassing data preprocessing, model development, deployment, and ongoing monitoring to ensure reliability and performance. Implement optimization techniques to enhance model efficiency and scalability.

Leverage cloud platforms such as Google Cloud Platform (GCP), Microsoft Azure, or Amazon Web Services (AWS) for deploying and scaling AI services. Utilize Python scientific computing libraries—including pandas, NumPy, scikit-learn, and matplotlib—for data analysis and model construction.

Apply MLOps best practices to streamline the development, deployment, and maintenance of machine learning models. Integrate advanced AI services such as speech-to-text, document AI, and other cognitive technologies to enrich solution capabilities.

Employ retrieval-augmented generation (RAG) techniques to boost AI system performance and versatility. Collaborate closely with cross-functional teams to define, design, and implement AI-driven features and products that address business needs.

Stay abreast of emerging AI and ML technologies, continuously exploring innovative applications to solve complex challenges. Communicate effectively with both technical and non-technical stakeholders, presenting ideas, progress, and results clearly and persuasively.

Required Qualifications
- Proven hands-on experience with Python scientific computing libraries such as pandas, NumPy, scikit-learn, and matplotlib.
- Strong understanding of the machine learning lifecycle and conventional ML models.
- Practical experience developing, fine-tuning, and deploying Generative AI models, including large language models and text-to-SQL architectures, in production environments.
- Solid knowledge of ML model optimization techniques to ensure high performance and scalability.
- Familiarity with MLOps practices and tools for efficient model lifecycle management.
- Experience working with cloud platforms like GCP, Azure, or AWS for AI service deployment and scaling.
- Understanding of retrieval-augmented generation (RAG) methods and their application in AI solutions.
- Experience integrating AI services such as speech-to-text, document AI, and other cognitive services.
- Strong foundation in mathematics and statistics relevant to machine learning.
- Excellent communication and collaboration skills to work effectively across teams.
- Passion for researching and applying emerging AI/ML technologies to solve real-world problems.

Preferred Qualifications and Benefits
While not explicitly stated, candidates with additional experience in advanced AI research, a background in software engineering, or prior involvement in large-scale AI deployments will be highly valued. We offer a collaborative work environment that encourages innovation and continuous learning, with opportunities to work on cutting-edge AI projects that impact business outcomes.

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This role is ideal for professionals passionate about advancing AI technologies and delivering scalable, production-ready AI solutions that drive business success.