Principal AI/ML Engineer; Language Model; TS/SCI; S
Listed on 2026-02-07
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IT/Tech
AI Engineer, Machine Learning/ ML Engineer
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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 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 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
- 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
- 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 Hugging Face and Lang Chain
- Experience with Computer Vision libraries such as OpenCV, Nerfstudio, Fifty One, 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…
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