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i4DM

Lead AI Engineer

i4DM, Millersville, Maryland, United States, 21108


Description

About the Company

Our core values of People Matter, Integrity, and a Commitment to Excellence drive all that we do. By joining us, you'll become a part of a fun and diverse team of talented and creative consultants who share the goal of using the latest technology to solve business challenges. We provide our clients with a dynamic mix of services and deliver focused solutions like no one else.

We're seeking talented and bright team players who are passionate about technology and want to work in a fast-paced, dynamic, and ego-free culture while applying a creative approach to problem-solving. Team members who like to grow their skill sets while solving challenging, real world business problems thrive.

About the Role

We are seeking a Lead AI Engineer who is passionate about cutting-edge technology and thrives in a dynamic and collaborative environment. As part of our team, you will lead the development of innovative AI solutions while working with a diverse and talented group of engineers, subject matter experts and data scientists. We're looking for a well-rounded team member to contribute to digital transformation efforts in the US Army.

In this role, you will apply creative problem-solving to some of our most complex challenges, including automating and optimizing business processes through AI-driven platforms. You'll spearhead the development and deployment of AI models, from deep learning and NLP to large language models (LLMs), across cloud platforms. Working closely with cross-functional teams, you will drive the automation of model deployment pipelines, standardize data processes, and deliver AI capabilities that unify and streamline operations. This is a unique opportunity to lead AI innovation in a culture that values creativity, collaboration, and continuous learning, while delivering impactful solutions to the Department of Defense.

RESPONSIBILITIES

AI Application Development:

Design, build and deploy advanced machine intelligence applications such as digital agents (chatbots) and pattern recognition systems for text, image, and speech recognition.Develop and optimize Natural Language Processing (NLP) systems, with a focus on entity extraction and machine learning-driven language understanding.Deep Learning Model Development:Design and implement deep learning models for various AI applications, including text classification, image recognition, and generative models.Perform machine learning optimization via feature selection, metrics analysis, and hyperparameter adjustment for enhanced model accuracy and efficiency.Large Language Models (LLM) & Retrieval-Augmented Generation (RAG):

Apply expertise in large language models (LLM) and Retrieval-Augmented Generation (RAG) to create scalable, high-performance language models that drive business and product innovation.Model Deployment & Real-Time Monitoring:

Deploy machine learning models into larger systems, ensuring seamless integration and monitoring real-time performance. Implement feedback loops to continuously optimize models based on production data.Platform Capability Development:

Develop Generative AI & Traditional AI platform capabilities on enterprise on-prem and cloud platforms.Build automation capabilities for ML and LLM model deployment on on-prem and cloud platforms (e.g., GCP-Vertex AI, Azure ML).Standardize model consumption and data pipeline deployment, enabling multiple Lines of Business (LOB) to utilize the deployed models efficiently.UI Development for AI Applications:

Lead the design and development of intuitive and responsive user interfaces for AI applications, ensuring smooth user interaction and visualization of AI-driven insights.Work closely with UX/UI designers and front-end developers to create interfaces that enhance the user experience of AI-powered tools such as chatbots and AI dashboards.Collaboration & Optimization:

Collaborate with Data Scientists to optimize the scoring pipeline for AI models, ensuring high-performance scoring and inferencing capabilities for ML models and LLMs.Work with product owners, DevSecOps teams, data scientists, and support teams to define and drive end-to-end model scoring pipelines, ensuring seamless deployment and scalability.Design, build and deploy artificial intelligence solutions that empower humans to make more informed decisions.Participate in day-to-day standups to contribute to platform capability development and ensure alignment across teams.Leadership & SME Guidance:

Provide Subject Matter Expertise (SME) guidance to data science teams on software engineering principles, model training and deployments, and platform capabilities.Lead AI use case delivery, collaborating with business subject matter experts, data scientists, data engineers, security engineers and LOB technology teams using standardized platform processes and capabilities.QUALIFICATIONS

Typically requires a minimum of 8 years of related experience with a Bachelor's degree; or 6 years and a Master's degree; or a PhD with 3 years' experience; or equivalent combination of related education and work experience.Expertise in entity extraction and advanced NLP techniques within machine learning frameworks.Strong experience in deep learning model design and development, including classification and generative models.Skilled in machine learning optimization, focusing on feature selection, metrics analysis, and hyperparameter tuning.Hands-on experience with large language models (LLM) and Retrieval-Augmented Generation (RAG).Proven ability to deploy AI models to Microsoft cloud platforms (CoPilot, Azure ML, and/or Amazon Bedrock), including real-time performance monitoring.Experience in building platform capabilities to automate ML/LLM model deployment and scaling, as well as standardizing data pipeline deployments for model consumption across various LOBs.Collaborate with data scientists to optimize model scoring pipelines and ensure high-quality model inferencing.Strong ability to collaborate across functions, including product management, DevOps, and data science teams, and lead AI use case delivery from concept to deployment.Preferred candidate will have significant substantive experience with mission IT-focused AI solutions.Preferred candidate will demonstrate experience and capability to advise the federal government on all aspects of the AI domain to implement and adopt innovative AI solutions.Military experienced candidates are encouraged to apply.Candidates may need to obtain Security Clearances.

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