Bison Group is seeking a Machine Learning Engineer to train, fine-tune and evaluate models for AI analysis tools. You will own the model training lifecycle, from dataset preparation through evaluation and deployment, and adapt models to domain-specific language and tasks. Hands-on model training experience is required; experience limited to hosted APIs or prompt engineering does not meet this requirement.
What you will do:- Train and fine-tune open-weight language models using supervised fine-tuning and parameter-efficient methods such as LoRA/QLoRA. Improve performance on domain terminology, task instructions and structured outputs.
- Build instruction and preference datasets from transcripts, surveys and reference materials.
- Clean, deduplicate and label data; generate and validate synthetic examples with subject matter.
- Train or fine-tune embedding and reranker models for retrieval-augmented generation (RAG).
- Measure retrieval quality for specialized terminology and acronyms.
- Adapt speech recognition, speaker diarization and voice activity detection models for noisy audio, varied accents and conversations with multiple speakers.
- Build offline evaluation suites and regression tests covering citation and attribution accuracy, hallucination rate and latency. Demonstrate improvements against established baselines before Quantize, export and serve trained models on on-premises GPUs and constrained hardware.
- Balance model quality against memory use, inference speed and throughput.
- Create reproducible training workflows with experiment tracking, versioned datasets, checkpoints and model cards. Package models and dependencies for deployment in environments without internet.
- Partner with product, UX, analysts and subject matter experts to define useful model behavior.
- Document experiments and decisions so teammates can retrain, evaluate and maintain models.
Requirements
- 3+ years of hands-on neural network training or fine-tuning. Ability to explain a project end to end, including data preparation, training decisions, evaluation results and deployment.
- Hands-on fine-tuning of a 7B+ parameter open-weight language model using supervised fine-tuning (SFT), LoRA/QLoRA or full fine-tuning, with PyTorch and Hugging Face Transformers/PEFT, NeMo or equivalent tools.
- Dataset construction skills, including cleaning, deduplication, formatting and labeling of text data, and judgment about whether data is suitable for training.
- Experience designing task-specific metrics and test sets, and diagnosing overfitting, catastrophic forgetting and data leakage.
- GPU training fundamentals, including mixed precision, gradient accumulation, checkpointing, memory budgeting and multi-GPU basics.
- Strong Python and Linux skills, including command-line work, CUDA environment management and dependency management without internet access.
- U.S. citizenship and eligibility to obtain and maintain a U.S. security clearance.
Preferred qualifications: - iOS development, especially on-device machine learning with Core ML or MLX.
- Training small language models or distilling larger models for edge and on-device use.
- Experience with NVIDIA NeMo or model serving with NIM/TensorRT-LLM.
- Preference tuning with DPO, ORPO or RLHF, or experience with reward modeling.
- Training embedding or reranker models for RAG applications.
- Speech recognition fine-tuning, speaker diarization or voice activity detection.
- Quantization and inference tooling such as GGUF, llama.cpp, vLLM, AWQ/GPTQ or MLX.
- Experience with ARM64 or other unified-memory platforms.
- Work in defense, intelligence or air-gapped environments; an active Secret clearance or higher.
- Familiarity with qualitative research data, including focus groups, surveys and interview.
Disclaimer: This position offers a wage or salary range based on market data and internal pay policies. This range is a good-faith estimate and may vary depending on qualifications, experience, and other factors. We do not request or use prior compensation history in making employment decisions. Any voluntary disclosure of prior wage information may be considered to support a higher offer but will not be used to justify a lower offer.
The Bison Group offers benefit options including medical, dental, vision, life, disability insurance, and accrued PTO including vacation, sick leave and holidays.
The listed pay range serves as a general guideline rather than a guaranteed salary. Final compensation is determined by a variety of factors including, but not limited to, role-specific responsibilities; candidate qualifications such as education, skills, and mission-aligned experience; market data, business considerations, internal equity, and any applicable legal or bargaining agreements (if any).
