Senior AI/ML Engineer

We are seeking a dynamic and experienced AI/ML Engineer to join our innovative team. The ideal candidate will have a strong background in machine learning and software engineering, with a proven track record of designing, developing, and optimizing predictive and classification models for various use cases. You will play a crucial role in leading the development of advanced AI/ML solutions, including Retrieval-Augmented Generation (RAG)-based applications, large language model (LLM) fine-tuning, and agent-based systems.

Key Responsibilities:

• Continuously learn and adapt to new domains, such as Oil & Gas Title, Leases, and Finance.
• Design, develop, and optimize machine learning models for prediction, classification, and other financial use cases.
• Collaborate closely with software engineers to integrate AI/ML models into production systems, ensuring seamless deployment and operation.
• Lead the design and development of RAG-based applications, LLM fine-tuning, and agent-based systems.
• Implement NLP techniques for Named Entity Recognition, relationship extraction, and document classification.
• Analyze and enhance the efficiency, scalability, and reliability of backend systems.
• Work within a cross-functional scrum team, responding quickly and effectively to evolving business needs.
• Stay current with the latest AI/ML research and advancements, applying new techniques to improve our products.
• Identify data-related capabilities and infrastructure requirements resulting from new and evolving product constructs, developing these capabilities cloud-natively.
• Write robust, idiomatic code and develop functional, performance, and system test suites.

Required qualifications : 

• A Bachelor's or Master’s Degree in Computer Science, Software Engineering, or a related field is preferred, but significant relevant experience will also be considered.
• 8+ years in AI/ML engineering with a focus on developing, testing, and optimizing machine learning models.

Skills:

• Tech Stack: Proficiency in Python (preferred), R, or similar programming languages.
• Data Handling: Expertise in working with large datasets, data preprocessing, and feature engineering.
• DevOps & Cloud: Familiarity with cloud platforms like Azure, AWS, GCP and experience with MLOps practices for deploying models in production.
• Database Knowledge: Proficient in both relational and No-SQL databases.
• Advanced Techniques: Experience in designing and developing RAG-based applications, fine-tuning LLMs, and implementing agent-based applications.
• NLP & Relationship Extraction: Skilled in Named Entity Recognition, document and text classification, and evaluating models for relationship extraction.
• Problem-Solving: Strong problem-solving skills, algorithmic thinking, and a solid foundation in system architecture.

Collaboration: Ability to work effectively in a cross-functional team environment, collaborating with data scientists, software engineers, and product managers.