Principal AI/ML Engineer (Large Language Model)

CACI InternationalAurora, CO
1d

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.

Requirements

  • BS in machine learning, computer science, mathematics, or related fields.
  • 10+ years of experience, preferably in software development or as a data scientist with 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.)
  • Active TS/SCI U.S. Government Security Clearance

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

  • Our employees value the flexibility at CACI that allows them to balance quality work and their personal lives.
  • We offer competitive compensation, benefits and learning and development opportunities.
  • Our broad and competitive mix of benefits options is designed to support and protect employees and their families.
  • At CACI, you will receive comprehensive benefits such as; healthcare, wellness, financial, retirement, family support, continuing education, and time off benefits.
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