Lead AI Engineer

4 weeks ago

Millersville, United States i4DM Full time
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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