LLM Engineer

Job Title: LLM Engineer

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Location:

[Location] (Opportunities for remote/hybrid/flexible work available)

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Reports to:

Head of LLM Engineering​

 

Role Purpose

We are looking for an experienced and innovative LLM (Large Language Model) Engineer to join our dynamic team at [Company Name], based in [Location] with flexible working arrangements, including remote or hybrid options. This role offers an exciting opportunity to push the boundaries of language model technology to drive significant impact within our products and services. As an LLM Engineer, you will develop, deploy, and optimize high-performing large language models that will shape the future of our AI capabilities, aligning with our mission to deliver cutting-edge solutions in the [Industry] sector.

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Company Overview

Summarize your company and it’s culture.[e.g. [Company Name] is a leading AI technology company specializing in developing advanced artificial intelligence solutions for [specific industry or application]. Our mission is to [company mission]. We foster a collaborative and inclusive work environment that encourages creativity and professional growth.] Include USPs and technical innovation or focus that will appeal to the ideal candidate [e.g. Recognized as one of the "Best Places to Work" by [Awarding Body], we are committed to excellence in AI technology.]

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Key Responsibilities

 

• Develop and Fine-Tune LLMs: Lead the design, training, and fine-tuning of large language models for applications that address specific business challenges and drive customer value.

• Collaborate Across Functions: Work closely with product managers, software engineers, and data scientists to integrate LLM capabilities seamlessly into our products, ensuring alignment with product goals and customer needs.

• Optimize Model Performance: Enhance model performance, focusing on efficiency, accuracy, and scalability while minimizing computational and energy costs.

• Research and Innovation: Continuously explore and evaluate the latest advancements in NLP, AI, and machine learning, applying cutting-edge techniques and frameworks to improve model effectiveness.

• Data Management and Processing: Oversee data collection, cleaning, labeling, and transformation processes to ensure high-quality datasets for training and fine-tuning models.

• Ethical AI and Compliance: Ensure all AI solutions comply with ethical standards, data privacy laws, and company policies, advocating for responsible AI practices.

• Mentorship and Knowledge Sharing: Provide technical guidance, mentorship, and training to team members and other departments on best practices in LLM development and deployment.

• Troubleshooting and Support: Diagnose, troubleshoot, and resolve issues related to model performance, deployment, and maintenance, providing ongoing support and improvements.

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Required Skills and Qualifications

• Proven experience in designing, developing, and deploying large language models, with a portfolio of past projects or contributions to LLM development.

• Advanced proficiency in Python and familiarity with libraries like TensorFlow, PyTorch, or Hugging Face Transformers; experience with other languages such as Java or C++ is a plus.

• Strong understanding of NLP frameworks, machine learning algorithms, and natural language processing techniques, including BERT, GPT, T5, and similar architectures.

• Working knowledge of cloud platforms (e.g., AWS, Google Cloud, Azure) and experience with distributed computing or parallel processing frameworks.

• Ability to translate complex problems into efficient and scalable solutions, with a high degree of attention to detail.

• Excellent interpersonal skills and ability to work effectively within cross-functional teams; capable of explaining complex technical concepts to non-technical stakeholders.

• Self-motivated with the ability to manage multiple projects and deliver results in a fast-paced environment.

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field; PhD is a plus.

• PhD in a relevant field or equivalent experience in LLM development.

• Familiarity with MLOps practices, including model monitoring, versioning, and automated deployment.

• Experience working with reinforcement learning or transfer learning for LLMs.

• Published research or contributions to the AI/NLP community is a strong advantage.

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Perks and Benefits:

Clearly outline the benefits and perks of the role.​

 

How to Apply:

End with a strong call to action encouraging candidates to apply. Include a direct link to the application page and provide contact information for further queries.

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Please ensure each job description includes all relevant information in compliance with local, state, and national laws. This includes:
 

 

• Salary Information: Provide a clear salary range to maintain transparency and meet legal requirements.

• Privacy Policies: Protect candidate privacy by following all applicable data protection and privacy laws.

• Equality & Non-Discrimination: Include an equal opportunity statement to uphold our commitment to a diverse, inclusive workplace that does not discriminate based on race, gender, age, disability, or any other protected characteristic.

• Accessibility: Make reasonable accommodations available for candidates with disabilities and include information on how they can request assistance throughout the hiring process.

• Environmental and Social Responsibility: If your company has sustainability initiatives or community engagement programs, mentioning them briefly can attract candidates who prioritize working for socially responsible employers.

• Transparent Hiring Process: Briefly explain the hiring process (e.g., “Our interview process typically includes three stages: an initial screening, a technical interview, and a final interview”) to help candidates know what to expect.