Principal AI/ML Engineer (Large Language Model)

CACI • Aurora, CO

11d • Onsite

About The Position

The Principal AI/ML Engineer will support the development of AI/ML algorithms in a multitude of disciplines from object detection/classification, natural language processing, reinforcement learning, and large language models. This role involves leading and mentoring a multidisciplinary team, applying Large Language Models (LLMs) to various applications, fine-tuning foundation models, building adaptors, applying retrieval augmented generation (RAG) techniques, building custom applications with LLM frameworks, deploying LLM solutions, and analyzing large multi-domain datasets. The engineer will also review publications to apply cutting-edge concepts and interface with leadership to communicate technical status.

Requirements

• Active TS/SCI with Adjudicated Polygraph
• BS in machine learning, computer science, mathematics, or related fields.
• 10+ years of experience, preferably in software development or as a data scientist
• 2+ years of building LLM applications using some of the following: Fine-tuning foundational models, Steering Techniques (e.g Sparse auto encoders, representation tuning), Building adapters to use foundational models (e.g. PEFT, llama factory), Prompt engineering techniques / Inference time techniques (e.g. chain of thought, tree of thoughts, etc.)
• Using Retrieval Augmented Generation techniques to populate and query vector databases (e.g. Weaviate, pinecone)
• Using LLM Frameworks (e.g. LangChain, DSPy)
• Using AI APIs ( e.g AWS Bedrock, OpenAI)
• Using LLM deployment frameworks (eg llama.cpp, vllm, tgi)
• Developing UIs with ReAct
• Experience leading an interdisciplinary team of researchers and software developers and working with a program manager to define project scope and schedule to ensure we meet project milestones as defined by our customers
• Experience with Python and data science / machine learning libraries (e.g. PyTorch, TensorFlow, Keras, OpenCV, NumPy, Pandas, Polars, scikit-learn, etc.)

Nice To Haves

• MS or PhD in machine learning, computer science, mathematics, or related fields.
• Experience leading an interdisciplinary team of researchers and software developers
• Experience with any of the following Computer Vision domains: Large Language Models and experience identifying ways to incorporate them into new areas and applications
• Applying Transformer-based architectures to domains in other areas outside of Natural Language Processing (NLP) such as computer vision
• Object detection algorithms such as YOLO and Faster-RCNN
• Natural Language Processing algorithms such as BERT
• Generative Adversarial Networks and Variational Autoencoders
• Reinforcement learning and familiarity with Gymnasium Gym, RLlib, and Stable Baselines
• Applying clustering algorithms and/or deep neural networks to real life problems
• Implementing tracking and pattern-of-life algorithms
• Experience with Machine Learning libraries and frameworks such as HuggingFace and LangChain
• Experience with Computer Vision libraries such as OpenCV, Nerfstudio, FiftyOne, etc.
• Experience with Linux
• Familiarity with using AWS cloud computing resources such as EC2, S3, Lambda, etc.
• Experience with any of the following additional languages: Java, C++, Rust, Go, and/or C#
• Experience implementing algorithms on the GPU in Python or C++ using CUDA and other CUDA libraries
• Experience with implementing tracking and pattern-of-life algorithms
• Experience in application deployment, virtualization, and containerization (e.g. Podman, Docker, Kubernetes, Rancher)
• Experience working with various Remote Sensing datasets (e.g. EO/OPIR/SAR images, passive RF, etc.)
• Experience shaping and writing proposals

Responsibilities

• Lead and mentor a multidisciplined team consisting of developers and researchers to implement machine learning algorithms to solve a broad set of challenges for our various customers
• Apply Large Language Models (LLMs) to a variety of applications within remote sensing such as tasking collections, identifying gaps in collection plans, analyzing patterns of life, and more.
• Fine tune foundation models and building adaptors for new applications (llama factory, PEFT)
• Apply retrieval augmented generation (RAG) techniques to data to populate and query vector databases (e.g. Weaviate)
• Build custom applications with LLM frameworks such as LangChain, DSPy
• Deploy LLM solutions across cloud-based and local resources using kubernetes (llama.ccp, vllm etc)
• Analyze large multi-domain datasets such as images, text and/or graph data, to identify statistically relevant features to build models that provide analysts with actionable data
• Review relevant publications to understand and apply cutting edge concepts to defense and commercial applications
• Interface with both internal and external leadership to communicate technical status

Benefits

• flexible time off
• robust learning resources
• competitive compensation
• competitive benefits
• learning and development opportunities
• comprehensive benefits such as; healthcare, wellness, financial, retirement, family support, continuing education, and time off benefits

What This Job Offers

• Job Type: Full-time
• Career Level: Principal