iCapital is powering the world’s alternative investment marketplace. Our financial technology platform has transformed how advisors, wealth management firms, asset managers, and banks evaluate and recommend bespoke public and private market strategies for their high-net-worth clients. iCapital services approximately $170 billion in global client assets invested in 1,392 funds, as of October 2023.

　　iCapital has been named to the Forbes Fintech 50 for six consecutive years (2018-2023); a three-time selection by Forbes to its list of Best Startup Employers (2021-2023); and a three-time winner of MMI/Barron’s Solutions Provider award (See link below).

　　Job Description  

　　iCapital'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. 

　　  Responsibilities 

　　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.  Qualifications 

　　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.   

　　The base salary range for this role is $150,000 to $200,000. iCapital offers a compensation package which includes salary, equity for all full-time employees, and an annual performance bonus. Employees also receive a comprehensive benefits package that includes an employer matched retirement plan, generously subsidized healthcare with 100% employer paid dental, vision, telemedicine, and virtual mental health counseling, parental leave, and unlimited paid time off (PTO).  

　　We believe the best ideas and innovation happen when we are together. We offer most employees the flexibility to work in the office three or four days.  Every department has different needs, and some positions will be designated in-office jobs, based on their function. 

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　　For additional information on iCapital, please visit https://www.icapitalnetwork.com/about-us  Twitter: @icapitalnetwork | LinkedIn: https://www.linkedin.com/company/icapital-network-inc | Awards Disclaimer: https://www.icapitalnetwork.com/about-us/recognition/ 

　　iCapital is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, gender, sexual orientation, gender identity, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.