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Machine Learning Engineer II (Model Training)

Pay
Pay not listedSimilar roles state $166K–$240K
Work setting
On-site — work setting source
Work setup in the employer’s posting: On-site
From the employer’s posting
Employment
Not stated

Before you apply

Work authorization
US citizens onlyUS citizenship and eligibility to obtain and maintain a US security clearance

What you’ll work on

Full posting
  • Fine-tune open-weight language models with SFT and LoRA/QLoRA

  • Build instruction and preference datasets from transcripts, surveys and reference materials

  • Build offline evaluation suites and regression tests for accuracy and hallucination

  • Quantize, export and serve trained models on on-premises GPUs and constrained hardware

  • Create reproducible training workflows with experiment tracking and model cards

From the employer’s posting
Train and fine-tune open-weight language models using supervised fine-tuning and parameter-efficient methods such as LoRA/QLoRA
Build instruction and preference datasets from transcripts, surveys and reference materials.
Build offline evaluation suites and regression tests covering citation and attribution accuracy, hallucination rate and latency.
Quantize, export and serve trained models on on-premises GPUs and constrained hardware.
Create reproducible training workflows with experiment tracking, versioned datasets, checkpoints and model cards.

What you’ll bring

All qualifications

Core experience

  • 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.
  • Experience designing task-specific metrics and test sets, and diagnosing overfitting, catastrophic forgetting and data leakage.
  • Strong Python and Linux skills, including command-line work, CUDA environment management and dependency management without internet access.

Preferred experience

  • Experience with NVIDIA NeMo or model serving with NIM/TensorRT-LLM.
  • Experience with ARM64 or other unified-memory platforms.
  • Familiarity with qualitative research data, including focus groups, surveys and interview.
Qualification wording
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.
Experience designing task-specific metrics and test sets, and diagnosing overfitting, catastrophic forgetting and data leakage.
Strong Python and Linux skills, including command-line work, CUDA environment management and dependency management without internet access.
Experience with NVIDIA NeMo or model serving with NIM/TensorRT-LLM.
Experience with ARM64 or other unified-memory platforms.
Familiarity with qualitative research data, including focus groups, surveys and interview.
Apply at The Bison Group

Posting record

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Actively hiringFirst seen by us 5 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 4, 20265 days ago
Recorded sightings
5
Last seen by us
Nov 9, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

$166K–$240K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 1,383 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 5

Early. Similar jobs usually come down between day 7 and day 72.

At The Bison Group, jobs usually come down by about day 8.

From 4,777 similar postings that came down, and 13 of The Bison Group’s. Coming down is not always a hire.

The Bison Group is hiring

5 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Hiring at a steady pace
  • Takes jobs down at a usual pace
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • Hugging Face
  • PyTorch
  • Transformers
Where the posting names them
- 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.
- 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.

Your next step

Complete your application on recruiting.paylocity.com. The employer’s form will show what is required.

Applying through Paylocity

  • “Upload your resume and we’ll automatically fill out your application”: the form fills itself from your file, so check it before sending.

Already applied? Track this application

Demand for ML Engineer roles

New ML Engineer postings at the employers we follow are up 13% over the last 6 weeks compared with the 6 before.

Weekly new ML Engineer postings at the same employers, from the week of August 17 to the week of November 2. The fewest in a week was 618, the most 1,131, and the latest week had 1,131.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 6 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

View original posting ↗

Description

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.

 

The Bison Group, LLC is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, pregnancy, national origin, age, genetic information, or protected veteran status and will not be discriminated against on the basis of disability.  If you’d like to view a copy of the company’s affirmative action plan for protected veterans/individuals with disabilities or our policy statement, please email EEO@bisongroupusa.com.  If you have a disability and you believe you need a reasonable accommodation in order to search for a job opening or to submit an online application, please e-mail Accessibiity@bisongroupusa.com.  This mailbox is created exclusively to assist disabled job seekers whose disability prevents them from being able to apply online. Only emails sent for this purpose will be returned. Emails left for other purposes, such as following up on an application or technical issues not related to a disability, will not receive a response.


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).

Source details

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Pay

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Location & working pattern

El Paso, TX

Working pattern and location restrictions need checking in the full posting.

Work authorization
- 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:

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