NLP/LLM Engineer job in Los Angeles, CA

Are you passionate about building the next generation of AI-powered solutions using cutting-edge NLP and LLM technologies? We are seeking an NLP/LLM Engineer to join our fast-growing AI team in Los Angeles, CA. In this role, you’ll design, train, and optimize state-of-the-art language models that power real-world applications. If you thrive in a research-driven, high-performance environment and are excited about working at the forefront of AI innovation, we want to hear from you.

Build Scalable AI Solutions in the Heart of Los Angeles

A leading technology company based in Los Angeles, CA is looking for an NLP/LLM Engineer to drive the development of scalable natural language applications. As a key member of the AI/ML team, you will apply deep learning and transformer-based architectures to solve complex language understanding problems. Ideal candidates will have hands-on experience with LLMs (e.g., GPT, BERT, LLaMA), a strong foundation in machine learning, and a passion for solving language-related challenges in production environments.

Key Responsibilities of the NLP/LLM Engineer – Artificial Intelligence & Machine Learning

Model Development & Optimization: Design, train, and fine-tune large-scale language models (e.g., GPT, BERT, LLaMA) for a variety of NLP tasks. Leverage transfer learning, reinforcement learning, and prompt engineering to improve model performance across different applications.

Research & Innovation: Stay at the forefront of advancements in NLP, deep learning, and generative AI. Experiment with novel architectures and techniques to enhance the capabilities of existing models and contribute to the broader AI research community.

End-to-End Product Integration: Collaborate with cross-functional teams including product managers, software engineers, and designers to integrate language models into production systems. Ensure models are scalable, secure, and optimized for real-time applications.

Data Engineering & Curation: Curate, preprocess, and manage large datasets for training and evaluation. Apply data augmentation, filtering, and synthetic data generation techniques to improve model robustness and fairness.

Evaluation & Metrics: Define and implement rigorous evaluation protocols using both standard benchmarks and task-specific metrics. Monitor performance, interpret results, and iterate on model designs based on empirical findings.

Ethical AI & Bias Mitigation: Proactively address issues of bias, fairness, and responsible AI deployment. Develop strategies to monitor model outputs, mitigate harmful behaviors, and ensure compliance with ethical guidelines.

Documentation & Knowledge Sharing: Maintain comprehensive technical documentation, experiment logs, and research findings. Contribute to internal wikis, whitepapers, and codebases to facilitate collaboration and transparency.

Tooling & Infrastructure: Utilize and improve internal ML infrastructure, training pipelines, and model serving systems. Leverage tools such as PyTorch, TensorFlow, Hugging Face, and cloud-based environments (e.g., AWS, GCP) to streamline workflows.

Mentorship & Team Collaboration: Support junior team members through code reviews, technical guidance, and knowledge sharing. Collaborate in a team environment focused on continuous learning and iterative improvement.

Security, Privacy & Compliance: Ensure adherence to data privacy laws and corporate compliance policies. Implement secure model handling, anonymization techniques, and data governance best practices.

What the Client is Looking for in You

As an NLP/LLM Engineer, the client is seeking a forward-thinking technologist with a deep understanding of natural language processing and large language models. You should be a hands-on engineer who can bring cutting-edge research into real-world applications, optimize model performance at scale, and collaborate across functions to build impactful AI solutions. This role requires a balance of scientific curiosity, engineering rigor, and product-minded thinking.

Deep Expertise in NLP and Machine Learning

The ideal candidate will have demonstrated experience with training, fine-tuning, and deploying transformer-based models such as BERT, GPT, T5, or LLaMA. A solid foundation in core NLP tasks—including tokenization, sequence labeling, summarization, question answering, and conversational AI—is essential. Experience with PyTorch, TensorFlow, Hugging Face Transformers, or similar frameworks is highly valued.

Passion for AI Innovation and Research

The client is looking for someone who stays on top of the latest AI research and is eager to experiment with new architectures, techniques, and training strategies. Whether you’re adapting SOTA models or contributing your own ideas to push the boundaries of what’s possible, your ability to bring novel thinking into practical implementation is critical.

Engineering Mindset with Production Focus

You should be comfortable working with production-grade ML pipelines and infrastructure. The client values engineers who understand how to take models from Jupyter notebooks to production APIs—ensuring scalability, low latency, and maintainability. Familiarity with cloud platforms (AWS, GCP, or Azure), MLOps tools, and containerized deployments is a strong plus.

Analytical Thinker with a Results-Driven Approach

Strong problem-solving skills and a data-first mindset are key. The client seeks someone who can interpret model results, debug training bottlenecks, and iterate quickly. Your ability to balance experimentation with execution will directly contribute to the success of AI-powered features.

Strong Collaboration and Communication Skills

This role requires close collaboration with product teams, data engineers, and UX designers. The ideal candidate will be able to translate complex technical insights into clear, actionable recommendations and contribute meaningfully to cross-functional product development discussions.

Commitment to Ethical and Responsible AI

The client is committed to building AI responsibly and values candidates who understand the ethical implications of language models. Experience identifying and mitigating bias, ensuring fairness, and aligning models with safety and compliance standards is a significant advantage.

Continuous Learner and Builder

The fast-moving world of LLMs demands a mindset of continuous learning. The client is looking for someone who thrives in dynamic environments, is excited by complex challenges, and is always looking for new ways to improve model performance and user outcomes.

FAQs About the Role – NLP/LLM Engineer – Artificial Intelligence

1. What are the key responsibilities of the NLP/LLM Engineer in this role?
As an NLP/LLM Engineer, you will design, train, fine-tune, and deploy large language models (LLMs) such as GPT, BERT, or LLaMA for various real-world NLP applications. You’ll be responsible for building robust ML pipelines, managing large-scale datasets, integrating models into production systems, and collaborating with cross-functional teams to deliver AI-driven solutions. Additional responsibilities include ensuring model fairness, ethical deployment, and ongoing performance optimization.

2. What qualifications and experience are required for this position?
The ideal candidate should have a strong foundation in machine learning, deep learning, and natural language processing. Experience with transformer-based models and libraries such as Hugging Face, PyTorch, or TensorFlow is highly desired. A degree in Computer Science, AI, or a related field is typically required, along with hands-on experience building and deploying NLP models in production. Experience working with cloud environments (AWS, GCP, Azure) and MLOps tools is a significant plus.

3. What kind of projects will I be working on?
You will work on a variety of NLP-driven applications, including but not limited to conversational AI, document summarization, semantic search, content generation, text classification, and information extraction. Projects may also include developing internal tools that leverage LLMs for code generation, support automation, or intelligent document processing.

4. What challenges can I expect in this role?
Challenges include managing large-scale model training and inference, optimizing for latency and scalability, ensuring responsible AI practices (bias mitigation, content filtering), and staying updated with the fast-evolving LLM landscape. You may also face data quality issues, limitations of current open-source models, and the complexities of model interpretability and evaluation.

5. How will my work impact the company’s AI strategy?
Your work will be central to the company’s AI-driven product innovation and customer experience. By developing and integrating state-of-the-art LLMs, you’ll enhance product capabilities, automate key processes, and enable new user experiences. Your contributions will directly support the organization’s vision to lead in AI adoption and responsible innovation.

6. What is the company’s culture and team structure like?
The company promotes a research-driven, engineering-first culture that encourages experimentation, continuous learning, and cross-disciplinary collaboration. You’ll work alongside experts in ML, data engineering, and product design in an agile, inclusive, and intellectually stimulating environment. Innovation, transparency, and ethical responsibility are core to the team’s culture.

What Remuneration Can You Expect from This Job?

As an NLP/LLM Engineer in Los Angeles, CA, you can expect a highly competitive compensation package reflective of the advanced skills, technical expertise, and impact this role brings to the organization. The remuneration typically includes:

1. Base Salary
For experienced NLP/LLM Engineers, the annual base salary generally ranges between $140,000 and $200,000, depending on your level of expertise, prior experience, and the size of the organization. Senior or lead engineers with significant LLM experience may command even higher salaries in competitive markets like Los Angeles.

2. Performance-Based Bonuses
In addition to a strong base salary, many companies offer annual bonuses tied to individual, team, and company-wide performance metrics. These bonuses may range from 10% to 25% (or more) of the base salary and are often linked to successful product launches, model performance milestones, or overall business growth powered by AI initiatives.

3. Equity & Stock Options
For roles within startups, scale-ups, or publicly traded tech firms, equity compensation is a common component. This can include stock options, RSUs (Restricted Stock Units), or token allocations, providing long-term financial upside based on company performance and valuation. In fast-growing AI companies, equity can represent a significant part of the total rewards package.

4. Retention Bonuses & Long-Term Incentives
To retain top AI talent, some organizations offer multi-year retention packages or long-term incentive plans (LTIPs). These incentives are structured to reward continued contributions over time, especially in high-impact roles such as LLM development.

5. Comprehensive Benefits
As an NLP/LLM Engineer, you can also expect access to a robust benefits package, which may include:

Health, dental, and vision insurance
401(k) with company matching or stock purchase plans
Flexible work hours and hybrid/remote options
Paid time off, including sick days, holidays, and vacation
Learning & development stipends or conference allowances
Mental wellness and AI ethics training programs

6. Signing Bonuses & Relocation Assistance
For candidates relocating or transitioning from competitive roles, companies may offer signing bonuses or relocation assistance packages, ranging from $5,000 to $25,000+, depending on the company size and the urgency of the hire.

Total Compensation Potential

When combining base salary, bonuses, equity, and benefits, total annual compensation for a skilled NLP/LLM Engineer can range from $160,000 to over $300,000. For candidates with rare expertise in generative AI, transformer architecture, and LLM optimization, offers at the higher end of the spectrum are not uncommon—especially in AI-forward organizations based in Los Angeles.

How to Apply

If you are a passionate and technically skilled NLP/LLM Engineer eager to work on cutting-edge language models and contribute to innovative AI solutions, we encourage you to apply for this exciting role in Los Angeles, CA. This is a unique opportunity to join a forward-thinking organization at the forefront of artificial intelligence, where your work will directly influence the next generation of intelligent systems.

To apply, please submit your updated resume along with a cover letter that highlights your experience in:

Developing and fine-tuning transformer-based models (e.g., GPT, BERT, LLaMA)
Building NLP pipelines and deploying models in production environments
Working with frameworks such as PyTorch, TensorFlow, or Hugging Face
Managing large-scale datasets and optimizing model performance
Collaborating in cross-functional teams and applying responsible AI practices

Feel free to include links to your GitHub, portfolio, or research publications that demonstrate your expertise in natural language processing, machine learning, or generative AI.

This position offers a high-impact opportunity to shape the future of AI applications across industries. Apply today to take the next step in your career as an NLP/LLM Engineer in Los Angeles, CA!

For more information or to explore similar opportunities, visit our LLM and Generative AI Engineer Recruiters page.

Job Category: LLM and Generative AI Engineer

Job Type: Full Time

Job Location: Los Angeles

NLP/LLM Engineer job in Los Angeles, CA