LLM Engineer – AI & Machine Learning Innovation

Are you passionate about pushing the boundaries of AI with cutting-edge Large Language Models (LLMs)? We are seeking a highly skilled LLM Engineer to join a forward-thinking technology team in San Francisco, CA. This is a unique opportunity to work at the forefront of generative AI, developing scalable language models that power intelligent applications. If you thrive in an innovative environment and want to shape the future of AI, this role is for you.

Drive the Next Generation of AI in San Francisco

A leading AI-first company in San Francisco, CA is looking for a talented LLM Engineer to build and optimize Large Language Models that solve real-world challenges. The ideal candidate will have a deep understanding of machine learning, NLP, and model deployment. This role offers the chance to collaborate with top-tier researchers and engineers while making a measurable impact through groundbreaking AI solutions. If you’re excited to turn research into reality, join us and help define the future of language intelligence.

Key Responsibilities of the LLM Engineer – San Francisco, CA

Model Development & Optimization:
Design, train, and fine-tune Large Language Models (LLMs) using advanced machine learning techniques. Leverage state-of-the-art architectures such as Transformers to build scalable and efficient AI systems for a variety of use cases.

Research & Innovation:
Stay at the forefront of NLP and AI research. Experiment with novel algorithms and architectures, contribute to internal knowledge bases, and publish findings to drive innovation within the company and the broader AI community.

Infrastructure & Deployment:
Collaborate with engineering teams to build robust ML pipelines for training and inference. Ensure efficient model deployment, versioning, and monitoring in production environments using MLOps best practices.

Cross-functional Collaboration:
Work closely with product managers, data scientists, and software engineers to understand requirements, define AI capabilities, and integrate LLMs into applications that deliver real-world value.

Data Management & Curation:
Identify and preprocess large-scale, high-quality datasets for training and evaluation. Implement strategies for data augmentation, filtering, and synthetic data generation to enhance model performance.

Performance Evaluation & Tuning:
Analyze model outputs, perform benchmarking, and fine-tune hyperparameters to improve accuracy, latency, and reliability. Use evaluation metrics like perplexity, BLEU, ROUGE, and others to measure model quality.

Ethical AI & Responsible Use:
Ensure that LLM outputs adhere to fairness, bias mitigation, and privacy standards. Incorporate safety protocols to minimize hallucination, toxic outputs, and misuse of AI capabilities.

Documentation & Reporting:
Maintain clear documentation of model architectures, training procedures, and experiment results. Provide regular updates and technical reports to stakeholders and leadership on progress, challenges, and outcomes.

Tooling & Frameworks:
Utilize modern ML frameworks like PyTorch, TensorFlow, Hugging Face Transformers, and distributed training tools to accelerate development. Contribute to internal tooling that improves efficiency and reproducibility.

Continuous Learning & Improvement:
Adapt to the rapidly evolving AI landscape by participating in conferences, workshops, and reading recent papers. Bring fresh perspectives and emerging techniques to enhance model development strategies.

What the Client is Looking for in You

As the LLM Engineer, the client is seeking a passionate technologist with deep expertise in Natural Language Processing and Machine Learning. You should be a highly analytical, innovative, and collaborative engineer capable of building, fine-tuning, and deploying cutting-edge Large Language Models that deliver real-world impact. If you’re driven by curiosity and thrive in a fast-paced R&D environment, this role is an excellent fit.

Proven Experience in LLM and NLP Engineering
The client is looking for an engineer with hands-on experience in developing and scaling LLMs such as GPT, BERT, or similar transformer-based architectures. You should be well-versed in building and fine-tuning models for a variety of tasks, including text generation, summarization, and conversational AI. Demonstrated success in applying these models in production environments is highly valued.

Deep Understanding of AI & Machine Learning Fundamentals
A solid foundation in machine learning algorithms, optimization techniques, and data structures is essential. The ideal candidate will have strong proficiency in Python and ML frameworks like PyTorch or TensorFlow. Familiarity with training large-scale models on distributed systems and handling large datasets is crucial.

Innovative Mindset with a Research-Driven Approach
The client seeks someone who can bridge the gap between research and application. You should be comfortable experimenting with novel techniques, evaluating new papers, and integrating cutting-edge advancements into your engineering workflow. A background in AI research, publications, or participation in academic/industry benchmarks is a strong plus.

Collaborative & Cross-Functional Team Player
The ideal LLM Engineer thrives in collaborative environments. You’ll be expected to work closely with product teams, data scientists, and software engineers to translate business needs into scalable AI solutions. The ability to clearly communicate complex technical concepts to both technical and non-technical stakeholders is important.

Strong Focus on Model Performance and Ethics
The client values engineers who not only build powerful models but also prioritize fairness, interpretability, and responsible AI use. You should be able to implement safety features, monitor model behavior, and mitigate potential risks such as bias, toxicity, and hallucinations in outputs.

Passion for Building Real-World AI Applications
A practical mindset and enthusiasm for deploying AI solutions in production are key. The client appreciates engineers who take ownership, iterate rapidly, and focus on delivering high-quality, user-centric solutions powered by LLMs.

Commitment to Continuous Learning
Finally, the ideal candidate is someone who stays up to date with the fast-evolving field of AI. Your willingness to continually explore new tools, frameworks, and research will play a critical role in keeping the company’s AI capabilities ahead of the curve.

FAQs About the Role – LLM Engineer – San Francisco, CA

1. What are the key responsibilities of an LLM Engineer in this role?
As an LLM Engineer, you’ll be responsible for developing, fine-tuning, and deploying state-of-the-art Large Language Models (LLMs) to solve complex real-world problems. Your work will include experimenting with model architectures, building training pipelines, optimizing performance, and collaborating with cross-functional teams to integrate AI solutions into scalable applications. You’ll also contribute to research, ensure responsible AI practices, and support continuous innovation in NLP technologies.

2. What qualifications and experience are required for this position?
The ideal candidate should have strong hands-on experience in machine learning, NLP, and deep learning—especially with transformer-based models like GPT, BERT, or similar. Proficiency in Python and frameworks like PyTorch or TensorFlow is essential. Experience with distributed training, large-scale data handling, and model deployment in production environments is highly valued. A degree in Computer Science, AI, or a related field is preferred; advanced degrees or relevant publications are a plus.

3. What technical skills should I bring to the role?
You should have a solid understanding of machine learning algorithms, natural language understanding/generation, and MLOps best practices. Expertise in model evaluation, training optimizations, dataset curation, and prompt engineering is important. Familiarity with tools such as Hugging Face Transformers, Ray, MLFlow, or Kubernetes for scalable deployment is advantageous.

4. What challenges can I expect in this role?
You may face challenges such as scaling models efficiently, managing model drift, addressing biases and hallucinations in outputs, and ensuring safe, ethical usage of AI. Working with massive datasets and integrating LLMs into real-time systems can also present performance and infrastructure challenges. The dynamic nature of the AI field means staying up to date with emerging research and evolving best practices is critical.

5. How will my work impact the organization and its products?
Your work will directly influence the company’s AI capabilities and product innovation. Whether it’s powering conversational interfaces, generating personalized content, or automating workflows, your contributions will play a key role in delivering intelligent, human-like experiences to users. You’ll help shape how the organization applies cutting-edge AI to stay competitive in a rapidly evolving tech landscape.

6. What is the company’s culture and work environment like?
The company promotes a collaborative, mission-driven, and research-oriented environment where experimentation and innovation are encouraged. Engineers are empowered to take ownership of their projects, challenge conventional thinking, and continuously improve. You’ll be surrounded by passionate peers who value transparency, intellectual curiosity, and ethical AI development.

What Remuneration Can You Expect from This Job?

As an LLM Engineer based in San Francisco, CA, you can expect a competitive and rewarding compensation package designed to attract top AI talent. The total remuneration typically reflects your expertise, experience, and contributions to the company’s AI innovation efforts.

1. Base Salary
The annual base salary for an experienced LLM Engineer in San Francisco ranges from $150,000 to $250,000, depending on qualifications, project scope, and the company’s funding stage. Senior engineers and specialists with deep experience in training and deploying large language models may command even higher base pay.

2. Performance-Based Bonuses
Many employers offer annual performance-based bonuses tied to individual contributions, model performance, project milestones, and team outcomes. These bonuses generally range from 10% to 25% of the base salary, with higher bonuses possible at fast-growing AI startups or tech giants.

3. Equity & Stock Options
In tech hubs like San Francisco, equity compensation is a standard component of engineer packages. Engineers may receive stock options, RSUs (Restricted Stock Units), or token equity stakes in early-stage ventures. The potential upside can be substantial, especially in high-growth or VC-backed startups.

4. Project & Milestone Incentives
Some companies offer additional incentives for key project completions, patent filings, published research, or production model deployments. These bonuses can range from $5,000 to $50,000 depending on the scope and impact of your work.

5. Comprehensive Benefits Package
LLM Engineers often receive a full suite of benefits, including:

Health, dental, and vision insurance
Employer-matched 401(k) or retirement savings plans
Life and disability insurance
Flexible paid time off (PTO) and holidays
Mental wellness and fitness reimbursement programs
Learning and development stipends

6. Remote Work Flexibility & Perks
While the position is based in San Francisco, many companies offer hybrid or remote work options. Additional perks may include commuter stipends, home office setup allowances, tech reimbursement, and attendance at AI conferences or workshops.

Total Compensation Potential

When factoring in salary, bonuses, equity, and perks, the total annual compensation for an LLM Engineer in San Francisco typically ranges from $200,000 to $450,000, with opportunities for even higher earnings at unicorn startups or well-funded AI labs. Those in leadership or staff-level roles with ownership of critical model architectures can see their compensation scale considerably.

How to Apply

If you’re an innovative and technically driven AI professional with a passion for building advanced Large Language Models, we invite you to apply for the LLM Engineer position in San Francisco, CA. This is a rare opportunity to work on cutting-edge NLP technologies, collaborate with world-class engineers, and shape the future of AI-driven applications.

To apply, please submit your updated resume and a cover letter detailing your experience in developing and deploying large-scale language models. Highlight your technical expertise in NLP, deep learning frameworks (such as PyTorch or TensorFlow), model optimization, and your contributions to AI research or production-level AI systems. If applicable, include links to your GitHub repositories, published research, or open-source contributions.

This role offers the chance to contribute to meaningful AI advancements, work with massive datasets, and help build the next generation of intelligent language systems. Apply today to be part of a mission-driven company at the forefront of machine learning innovation.

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

Job Category: LLM and Generative AI Engineer

Job Type: Full Time

Job Location: San Francisco

LLM Engineer job in San Francisco, CA