AI Engineer

The AI Engineer role is responsible for oversight of the development and administration of data-centered projects that ultimately improves current processes and promotes the company's expansion. With deep knowledge and expertise in utilizing machine learning to solve complex, real-world problems, the incumbent in this role recommends, and completes data-driven projects which are geared at furthering the company's interests. He/She pilots the development of cutting-edge Artificial Intelligence (AI) and Machine Learning (ML) driven solutions based on a rich stream of legal documents, statutes, claims, payer, and behavioral data. The role operates in a highly collaborative environment of data scientists, AI/ML engineers, domain experts and business leaders to deliver analytics products that have the potential to fundamentally alter how legal services are thought about and delivered in a large scale.

ESSENTIAL JOB DUTIES/RESPONSIBILITIES:

• Develops complex algorithms and statistical predictive models by determining analytical approaches and modeling techniques to evaluate scenarios and potential future outcomes.
• Performs and leads the analysis of both structured and unstructured data to address various complex business challenges, employing advanced statistical methods, and specialized industry or organizational expertise.
• Designs, develops, and deploys GenAI models, focusing on cognitive architectures, knowledge graph embedding, and multimodal learning.
• Implements and manages MLOps and LLMOps pipelines ensuring efficient and automated model training, testing, deployment, and monitoring.
• Integrates ML models with larger systems, including cloud-based infrastructure, software applications, and data platforms.
• Stays up to date with the latest advancements in GenAI, ML, MLOps, LLMOps, and apply this knowledge to drive innovation and improvement in our AI technology stack.
• Applies analytical rigor and statistical/ML methods to analyze large amounts of data using advanced statistical techniques.
• Manages large and complex analytical projects from data exploration, model building, performance evaluation and testing.
• Behaves as mentor to junior team members to provide technical advice.
• Collaborates with business partners to develop technical/business approaches and new or enhanced technical tools.
• Interacts with internal and external peers and management to share highly complex information related to areas of expertise and/or to gain acceptance of new or enhanced technology/business solutions.
• Identifies meaningful insights from "big data" sources, assists in the coordination of various research initiatives and serves as an internal consultant in identifying opportunities to improve decision making through the application of analytical concepts and techniques.
• Performs other duties as assigned and modified at manager's discretion.

KNOWLEDGE, SKILLS, AND ABILITIES:

• Astute business acumen and acuity.
• Expert knowledge and understanding of ML fundamentals including classical ML, deep learning techniques, and LLMs.
• Excellent verbal communication skills, including the ability to articulate complex concepts to both technical and non-technical audiences.
• Superb interpersonal, organization, time-management, and coordination skills.
• Task-oriented with an ability to set goals and complete deliverables.
• Outstanding supervision and mentorship abilities.
• Capacity to foster a healthy, stimulating work environment that frequently harnesses teamwork.
• Demonstrated aptitude in Python with hands-on experience implementing production machine learning systems.
• Skilled with relational databases, programming languages, web app frameworks and libraries such as MS SQL, Python, C#, React, scikit-learn, TensorFlow, PyTorch, Keras, Hugging Face, OpenCV, NLTK, Spacy, LangChain and shell scripting.
• Mastery skills in Microsoft Office Suite products including Word, Excel, PowerPoint, and Outlook, plus a variety of other word-processing, spreadsheet, database, e-mail, and presentation software.
• Spoken and written fluency in English.
• This job requires the use and exercise of independent judgment.

EDUCATION AND EXPERIENCE CRITERIA:

• Master's or PhD degree in a quantitative field such as: Statistics, Engineering, Computer Science, AI/ML, Data Science required OR experience may be considered in lieu of the required education on a year-for-year basis.
• 5+ years of experience in AI/ML engineering, Data science, software development, or a related field, with a focus on GenAI and ML.
• Strong understanding of advanced mathematics, statistics, programming, data handling, ML algorithms and predictive analytics.
• A minimum of 2 years' experience using tools in at least one cloud computing platform such as Amazon Web Services, Microsoft Azure, or Google Cloud Platform.
• Experience with DevOps, containerization (e.g., Docker), and agile development methodologies.
• Certified Analytics Professional (CAP) preferred.