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Assistant Llm Trainer Jobs (NOW HIRING)

PenFed Credit Union

LLM Specialist

Mclean, VA · On-site

$16.50 - $21.75/hr

Support AI literacy efforts and enterprise training initiatives. * Serve as a trusted advisor and ... * Assist with internal audits, regulatory examinations, and independent reviews related to AI ...

Bright Vision Technologies

LLM Prompt Specialist

$100K - $150K/yr

Exposure to product domains such as customer support, coding assistants, or analytics agents ... This commitment extends to all aspects of employment, including recruitment, hiring, training ...

MSRCosmos

AI Solution Architect

Bellevue, WA · On-site

$71 - $93.75/hr

... assistants LLM APIs prompt engineering costperf controls Azure AI Search vector search hybrid retrieval custom scoring reranking Azure ML training deployment model registry pipelines Cognitive ...

Agoda

Technical Product Manager, LLM/ML Domain

Seattle, WA · On-site

$190K - $219K/yr

... training, and internal evangelism • Collaborate with engineering to level up Agoda's platforms to ... assistants and autonomous agents • Ensure platform APIs, tooling, and abstractions enable ...

Agoda

Technical Product Manager, LLM/ML Domain

Manhattan, NY · On-site

$183K - $212K/yr

... training, and internal evangelism • Collaborate with engineering to level up Agoda's platforms to ... assistants and autonomous agents • Ensure platform APIs, tooling, and abstractions enable ...

Agoda

Technical Product Manager, LLM/ML Domain

Boston, MA · On-site

$181K - $209K/yr

... training, and internal evangelism • Collaborate with engineering to level up Agoda's platforms to ... assistants and autonomous agents • Ensure platform APIs, tooling, and abstractions enable ...

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Assistant Llm Trainer information

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How much do assistant llm trainer jobs pay per year?

As of Sep 15, 2026, the average yearly pay for assistant llm trainer in the United States is $42,039.00, according to ZipRecruiter salary data. Most workers in this role earn between $24,000.00 and $50,500.00 per year, depending on experience, location, and employer.

What is an assistant LLM trainer?

Assistant LLM Trainers are professionals who help develop, train, and fine-tune large language models (LLMs) used in artificial intelligence applications. They assist in tasks such as data collection, annotation, model evaluation, and iterative improvement of AI models. Their work ensures that LLMs become more accurate, ethical, and aligned with user expectations. Assistant LLM Trainers often collaborate with data scientists, engineers, and research teams to provide feedback and improve model performance.

What are the key skills and qualifications needed to thrive as an assistant LLM trainer?

To thrive as an Assistant LLM Trainer, you need a solid understanding of machine learning concepts, natural language processing, and a relevant degree in computer science or a related field. Familiarity with Python, deep learning frameworks like TensorFlow or PyTorch, and experience with data annotation tools are typically required. Strong analytical thinking, attention to detail, and effective communication skills help in refining data quality and collaborating with cross-functional teams. These skills are crucial for developing high-quality language models and ensuring the success of AI-driven projects.

What are some common challenges faced by assistant LLM trainers when preparing data for model training?

Assistant LLM Trainers often face challenges related to data quality and consistency, as preparing large and diverse datasets for language model training requires careful attention to annotation guidelines and error checking. Balancing the need for comprehensive, unbiased data with tight deadlines can also be demanding. Additionally, effective collaboration with data scientists and senior trainers is essential to ensure that the datasets align with project goals and meet technical standards. Over time, this experience helps build strong analytical and teamwork skills, which are valuable for career advancement in AI and machine learning roles.
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Infographic showing various Assistant Llm Trainer job openings in the United States as of September 2026, with employment types broken down into 2% As Needed, 75% Full Time, 21% Part Time, and 2% Contract. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution, with an average salary of $42,039 per year, or $20.2 per hour.

Senior Machine Learning Engineer, Speech & LLM Training Data

Overland Park, KS • On-site

Propio Language Services
Translation Services • 51 - 200 employees
Learn more about Propio Language Servicesexternal

$111K - $133K/yr

Full-time

Posted 7 days ago

Job description

Job Type
Full-time
Description
Propio Language Services is one of the top 5 providers high-quality, real-time multilingual interpretation, translation, and localization services, operating at 9-figure scale across healthcare, legal, and other industries. We are driven by a passion for cutting-edge technology and exceptional service, building seamless experiences that bridge communication gaps across languages, cultures, and modalities.
Propio is hiring a Senior Machine Learning Engineer, Speech & LLM Training Data to transform large volumes of multilingual conversational audio into high-quality training and evaluation datasets. This hands-on role owns audio processing, dataset curation, annotation and QA workflows, model training, and evaluation for our multilingual speech, translation, and conversational AI systems.
Key Responsibilities:
  • Define the data roadmap for multilingual speech, translation, multimodal LLMs, and conversational AI.
  • Build audio-processing pipelines covering resampling, channel handling, VAD, diarization, language identification, transcription, alignment, and quality filtering.
  • Build dataset pipelines for cleaning, deduplication, PII/PHI redaction, quality scoring, sampling, balancing, versioning, and lineage.
  • Design annotation guidelines, QA rubrics, golden datasets, and reviewer workflows.
  • Build evaluation datasets, analyze model failures, and translate performance gaps into targeted data improvements.
  • Run training, fine-tuning, post-training, and evaluation experiments, including SFT, preference data, DPO/RLHF-style workflows, and synthetic data generation.
  • Productionize secure, traceable, and reproducible data and ML workflows on AWS.

Requirements
Qualifications:
  • Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, Electrical Engineering, Computational Linguistics, or a related field, or equivalent practical experience.
  • 5+ years of experience in ML engineering, speech/audio ML, ML data engineering, NLP, or LLM training-data workflows.
  • Strong hands-on experience with Python, SQL, Linux, Git, and Docker.
  • Experience training or evaluating models using PyTorch, Hugging Face, or comparable ML frameworks.
  • Experience with FFmpeg and audio-processing libraries such as TorchCodec, torchaudio, librosa, or equivalent tools.
  • Experience with speech-processing tasks such as VAD, diarization, ASR, forced alignment, language identification, and audio-quality analysis.
  • Experience with Databricks/Spark, Parquet/Arrow, and large-scale dataset pipelines.
  • Working knowledge of AWS S3, SageMaker, Glue, Step Functions, IAM, and KMS.
  • Experience with an annotation platform such as Labelbox, Label Studio, Scale AI, Prodigy, Argilla, or custom internal tooling.
  • Experience with experiment tracking and data versioning tools such as MLflow, Weights & Biases, DVC, Delta Lake, or LakeFS.
  • Experience with multilingual speech, translation, annotation workflows, and evaluation datasets.

Preferred Qualifications:
  • Experience with multilingual telephony, healthcare, interpretation, or call-center audio.
  • Experience with tools such as Silero VAD, pyannote, WhisperX, NeMo, Kaldi, or equivalent speech technologies.
  • Experience with distributed processing or training using Ray, PySpark, or similar frameworks.
  • Experience with HIPAA, PHI/PII redaction, and secure data governance.
  • Experience with low-resource languages, accents, dialects, and code-switching.
  • Experience with synthetic data, active learning, weak supervision, or LLM-as-judge evaluation.

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Notice of AI Use in Job Application Review
As part of our commitment in creating a fair, efficient, and consistent hiring process we may use artificial intelligence (AI) to help our recruiting teams organize, summarize, and analyze information provided by candidates, including resumes, application responses, and other materials submitted during the application process.AI may be used to identify patterns, highlight relevant skills, and experience, and assist in comparing a candidate's qualifications with the requirement of a specific role. These tools are to improve efficiency and consistency while supporting more informed hiring decisions, which will ultimately be made by the hiring team.

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