← Serch more jobs

Staff AI/ML Engineer (Large Language Model) (TS/SCI) {S}

LinkedIn ARKA Group, LP King of Prussia, PA
Not Applicable Posted April 2, 2026 2 variants Job link
Thinking about this job
Not Met Priorities
What still needs stronger evidence
Requirements
  • 8+ 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, pgvector)
  • Using LLM Frameworks (e.g.
  • LangChain, DSPy, Microsoft Agent Framework)
  • 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.
  • NumPy, Pandas, Polars, scikit-learn, etc.)
  • Experience contributing on a team using version control (e.g. git, GitLab, Bitbucket)
  • Active TS/SCI U.S.
  • Experience leading an interdisciplinary team of researchers and software developers
  • Experience with any of the following:
  • Large Language Models and experience identifying ways to incorporate them into new domains and applications
  • Applying Transformer-based architectures to domains in other areas outside of Natural Language Processing (NLP) such as computer vision
  • Natural Language Processing algorithms such as BERT
  • Reinforcement learning and familiarity with Gymnasium Gym, OpenEnv, TorchRL, 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 GenAI Ops techniques (e.g.
  • LLM-as-a-judge) and frameworks (e.g.
  • LangFuse, MLFlow, Arize Phoenix)
  • Experience with Machine Learning libraries and frameworks such as HuggingFace and LangChain
  • Experience with Linux
  • Experience with CUDA and Python libraries such as CuPy, Numba, CuSignal, CuDF, etc.
  • 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 in application deployment, virtualization, and containerization (e.g.
  • Podman, Docker, Kubernetes, Rancher)
  • Experience shaping and writing proposals
Preferred Skills
  • Government Security Clearance Preferred Qualifications
  • M.S. 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:
  • Large Language Models and experience identifying ways to incorporate them into new domains and applications
  • Applying Transformer-based architectures to domains in other areas outside of Natural Language Processing (NLP) such as computer vision
  • Natural Language Processing algorithms such as BERT
  • Reinforcement learning and familiarity with Gymnasium Gym, OpenEnv, TorchRL, 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 GenAI Ops techniques (e.g.
  • LLM-as-a-judge) and frameworks (e.g.
  • LangFuse, MLFlow, Arize Phoenix)
  • Experience with Machine Learning libraries and frameworks such as HuggingFace and LangChain
  • Experience with Linux
  • Experience with CUDA and Python libraries such as CuPy, Numba, CuSignal, CuDF, etc.
  • 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 in application deployment, virtualization, and containerization (e.g.
  • Podman, Docker, Kubernetes, Rancher)
  • Experience shaping and writing proposals
Education
  • (Not required) – B.S. in machine learning, computer science, mathematics, or related fields
  • (Not required) – 8+ years of experience, preferably in software development or as a data scientist with 2+ years of building LLM applications using some of the following:
  • (Not required) – M.S. or PhD in machine learning, computer science, mathematics, or related fields