Principal AI​/ML Engineer; Language Model; TS​/SCI; S

Job Category
: ENG

Requisition Number
: PRINC
002818

• Posted :
  April 5, 2025
• Full-Time
• On-site

Showing 1 location

Aurora, CO 80011, USA

ARKA Group L.P. (“ARKA”) is an advanced technologies company serving the U.S. military, intelligence community, and commercial space industry delivering next-generation solutions to support the national security space enterprise. Built on more than six decades of excellence, ARKA brings modern approaches and a culture of innovation to the challenges of today.

Join the ARKA team to learn how Beyond Begins Here. Discover your next career opportunity now!

Position Overview:

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.

We offer generous relocation benefits for eligible candidates.

In support of work/life balance, many positions are available for a flexible schedule within the pay period. Ask us about the opportunity for flex scheduling if that’s of interest to you.

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 adapters 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 Lang Chain, 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

Required Qualifications:

• 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. Lang Chain, DSPy)
  • Using AI APIs (e.g AWS Bedrock, OpenAI)
  • Using LLM deployment frameworks (eg llama.cpp, vllm, tgi)
  • Developing UIs with Re Act
• 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, Tensor Flow, Keras, OpenCV, Num Py, Pandas, Polars, scikit-learn, etc.)
• Active TS/SCI U.S. Government Security Clearance

Preferred Qualifications:

• 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…