This FinTech's AI/ML team is developing cutting edge solutions to establish a unique competitive edge for the firm. As a senior AI/ML - NLP Engineer on our team, you will be responsible for designing, developing, and implementing AI/ML models for natural language processing (NLP) applications. This would involve working with large datasets, selecting appropriate algorithms and techniques, training or fine-tuning models to achieve optimal performance, and deploying and monitoring model performance in production. You will be working in a collaborative team environment across product management, data engineering, and software engineering teams. If you are passionate about leveraging machine learning techniques to drive innovation and have a strong background in developing scalable solutions, we would love to hear from you.
Design, develop, train, and deploy AI/ML models to solve business problems through a full development and production cycle in the FinTech domain.
Evaluate and compare the performance of different AI/ML algorithms and models.
Utilize and improve Machine Learning Operations (MLOps) pipelines and procedures to ensure efficiency, scalability, and maintainability.
Ensure the reliability, robustness, and scalability of machine learning models in production environments.
Collaborate with cross-functional teams, including product managers and full stack engineers, to deliver scalable machine learning solutions.
Understand business requirements, communicate with stakeholders, and mentor junior team members.
4-6+ (mid-career) years of experience as a hands-on data scientist or AI/ML engineer in AI/ML/DS fields.
Advanced degree (Masters, PhD) in a relevant field (AI/ML/DS, mathematics, computer science, etc.).
Solid understanding of Natural Language Processing techniques, including text classification, named entity recognition, and information extraction.
Experience working with Large Language Models, such as GPT-4, Liama 2, and other commercial or open-source models in production environment.
Proficiency in programming languages commonly used in NLP, such as Python, and libraries/frameworks like TensorFlow, PyTorch, or spaCy and strong understanding of software engineering principles and best practices.
Strong knowledge of NLP techniques, including text data preprocessing (tokenization, stemming, and text normalization, etc.) and information extraction (summarization, and question answering, etc.)
Knowledge of machine learning algorithms and statistical techniques, their limitations and implementation challenges
Experience with cloud platforms and distributed computing environments for NLP tasks, such as AWS, Google Cloud, or Azure
Experience with software development best practices, including source control (Git), CI/CD pipelines, testing, and documentation.
Excellent problem-solving skills and the ability to work independently and collaboratively in a fast-paced, agile environment.
Strong communication skills and the ability to effectively articulate technical concepts to both technical and non-technical audiences.
Nice to Haves
Publications, conference talks, and/or patents in AI/ML/DS or related fields
Experience with data visualization tools and techniques to effectively communicate and present findings.
Experience with data transformation tool (such as dbt) and orchestration tool (such as Airflow).
Portfolio of personal projects on Github, BitBucket, Google Colab, Kaggle, etc.
Experience working in Finance or Financial Technology (FinTech). Understanding of regulatory and compliance requirements in the financial industry and their implications for machine learning applications.