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Language Model Jobs (NOW HIRING)

Oxy

Senior AI Language Model Engineer

Houston, TX · On-site

$99K - $137K/yr

Design workflows for language model deployment. Perform prompt engineering, pre-processing, and post-processing to optimize output suitability. * Fine-tune and optimize multi-agentic systems to ...

Oxy

Senior AI Language Model Engineer

Houston, TX · On-site

$99K - $137K/yr

Design workflows for language model deployment. Perform prompt engineering, pre-processing, and post-processing to optimize output suitability. * Fine-tune and optimize multi-agentic systems to ...

NVIDIA

Senior Vision Language Model Engineer

Santa Clara, CA · On-site

$121K - $167K/yr

We are seeking a senior vision language model engineer to design and build agentic data and training workflows for Autonomous Vehicles, Robotics, and Medical applications. The right person for this ...

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How much do language model jobs pay per hour?

As of Jun 24, 2026, the average hourly pay for language model in the United States is $31.37, according to ZipRecruiter salary data. Most workers in this role earn between $18.99 and $39.18 per hour, depending on experience, location, and employer.

What are language models?

Language models are artificial intelligence systems designed to understand, generate, and manipulate human language. They are trained on vast amounts of text data to predict the next word in a sequence, answer questions, write content, translate languages, and perform other language-related tasks. Modern language models, such as those based on deep learning, have revolutionized natural language processing by enabling more accurate and context-aware interactions between humans and machines.

What is the difference between Language Model vs Data Scientist?

AspectLanguage ModelData Scientist
Required CredentialsNone specific; knowledge of NLP and AI concepts helpfulBachelor's or higher in Data Science, Statistics, or related fields
Work EnvironmentAI development teams, research labs, tech companiesBusiness, finance, healthcare, and various industries
Employer & Industry UsageUsed in AI applications, chatbots, content generationAnalyzing data, building models, providing insights

While both roles involve working with data and AI, a Language Model is an AI system designed to understand and generate human language, often developed by AI engineers. A Data Scientist analyzes data to extract insights and build predictive models, often utilizing language models as tools. Understanding the differences helps clarify career paths and job expectations in the AI and data fields.

What are the key skills and qualifications needed to thrive as a Language Model, and why are they important?

To thrive as a Language Model Engineer, you need a strong background in computer science, machine learning, and natural language processing, often supported by a relevant degree. Experience with frameworks like TensorFlow or PyTorch, and familiarity with large-scale data processing tools, are typically required. Strong analytical thinking, collaboration, and problem-solving skills help in designing effective models and working with cross-functional teams. These capabilities are crucial for developing performant and accurate language models that meet complex real-world communication needs.

What are the common challenges faced by professionals working on language model development teams?

Professionals developing language models often encounter challenges such as managing large datasets, addressing biases in training data, and optimizing model performance while balancing computational resources. Collaboration with cross-functional teams—including data scientists, engineers, and domain experts—is essential to ensure the model's accuracy and relevance. Additionally, staying current with rapid advancements in AI research and maintaining responsible AI practices are crucial aspects of the role.
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Language Model jobs near you
Infographic showing various Language Model job openings in the United States as of June 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, 1% Temporary, and 2% Contract. Highlights an 91% Physical, 1% Hybrid, and 8% Remote job distribution, with an average salary of $65,246 per year, or $31.4 per hour.

Research Scientist - Vision Language Model

Institute of Foundation Models

Sunnyvale, CA

Full-time

Posted 25 days ago

Job description

About the Institute of Foundation Models

We are a dedicated research lab for building, understanding, using, and risk-managing foundation models. Our mandate is to advance research, nurture the next generation of AI builders, and drive transformative contributions to a knowledge-driven economy. 

As part of our team, you’ll have the opportunity to work on the core of cutting-edge foundation model training, alongside world-class researchers, data scientists, and engineers, tackling the most fundamental and impactful challenges in AI development. You will participate in the development of groundbreaking AI solutions that have the potential to reshape entire industries. Strategic and innovative problem-solving skills will be instrumental in establishing MBZUAI as a global hub for high-performance computing in deep learning, driving impactful discoveries that inspire the next generation of AI pioneers.

Position Summary
As a Research Scientist in the Vision Language Model (VLM) team, your role will be central to advancing state-of-the-art multimodal foundation models that integrate visual understanding, reasoning, and agentic capabilities. You will work on the research and development of large-scale VLM systems, spanning model architectures, data recipes for pre-training and post-training, and evaluation benchmarks. The role combines cutting-edge research with practical engineering, emphasizing large-scale data processing, filtering, and weighting pipelines, distributed training systems, and reinforcement learning algorithms and systems for multimodal reasoning and agent development.
Key Responsibilities

  • Research and development of next-generation Vision Language Models across pre-training, instruction tuning, reasoning, and agents.

  • Develop novel architectures and training methodologies for integrating visual understanding, language reasoning, and tool-use capabilities.

  • Research efficient multimodal learning techniques, including data-efficient training, long-context modeling, model modularity, and inference optimization.

  • Build and improve large-scale multimodal datasets, synthetic data generation pipelines, and evaluation benchmarks for VLM capabilities.

  • Investigate multimodal reasoning, agentic behavior, OCR, grounding, document understanding, chart understanding, and visual question answering capabilities.

  • Contribute to technical reports, research publications, and open-source software.

  • Represent MBZUAI at research conferences and industry events, showcasing advancements in multimodal foundation models and large-scale AI systems.

  • Mentor junior researchers and collaborate across teams to drive impactful research initiatives.

Academic Qualifications
PhD or equivalent research experience in Machine Learning, Computer Vision, Natural Language Processing, or Multimodal AI.
Salary Range
 
The posted salary range represents the company’s good faith estimate of the compensation for this position upon hire. The actual compensation offered may vary within this range depending on individual qualifications, including but not limited to relevant skills, experience, education, certifications, geographic location, and specific business needs.  

Professional ExperienceMinimum  

  • Experience working with large language models and/or vision-language models, including pre-training, fine-tuning, evaluation, or inference.

  • Strong Python and PyTorch development skills for large-scale machine learning research.

  • Experience with distributed training systems and large-scale model optimization.

  • Familiarity with multimodal datasets and data processing pipelines involving images, text, and video.

  • Understanding of modern deep learning architectures, including Transformers, attention mechanisms, and multimodal fusion techniques.

  • Experience with ML infrastructure, including model evaluation, debugging, optimization, and large-scale experimentation.

  • Problem-solving and research skills with the ability to independently drive research/engineering projects.

  • Effective communication and collaboration skills for working across research and engineering teams.


Preferred Skills

  • Hands-on experience training or fine-tuning large Vision Language Models or multimodal foundation models at scale.

  • Experience with distributed learning frameworks and infrastructure such as PyTorch Distributed, Megatron, Triton, or CUDA.

  • Research experience in multimodal reasoning, agentic systems, tool use, OCR, grounding, document understanding, or multimodal retrieval.

  • Experience with synthetic data generation, multimodal data curation, or automated evaluation frameworks for VLMs.

  • Familiarity with efficient training and inference techniques such as FlashAttention, quantization, tensor parallelism, pipeline parallelism, or memory optimization.

  • Experience contributing to open-source ML software and large-scale research codebases.

  • Strong publication record in leading AI conferences such as NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, ACL, EMNLP, or related venues.

  • Experience collaborating across research, infrastructure, and product-oriented teams to deliver state-of-the-art multimodal systems.