Job Overview

Accenture is hiring an LLM Model Developer in Hyderabad for a full-time AI and machine learning opportunity focused on Large Language Models. The role is centered on adapting language models for specific domains and use cases through instruction fine-tuning, domain adaptation, data preparation, performance evaluation, and iterative model improvement.

The position is suitable for an experienced AI/ML professional who understands how language models are developed and refined and can work independently on model-related problems. The developer will collaborate with cross-functional teams to move model improvements toward production while also contributing technical knowledge within the team.

Key Responsibilities

• Develop and refine Large Language Models to improve their relevance and performance for defined domains and instructions.
• Apply appropriate fine-tuning approaches to adapt models for specific requirements.
• Analyze model behavior and performance to identify opportunities for improvement.
• Experiment with training data, preprocessing approaches, and model adaptation techniques.
• Evaluate model outputs and use performance findings to guide further improvements.
• Collaborate with cross-functional engineering and business teams when integrating model enhancements into production environments.
• Contribute technical solutions to model development and related project challenges.
• Document development methods, experiments, findings, and lessons learned for team knowledge sharing.
• Participate actively in technical discussions and contribute ideas to improve project outcomes.
• Support junior team members by sharing knowledge and providing guidance on model development activities.
• Work toward becoming a subject matter expert in Large Language Models and related development practices.

Required Skills

Strong proficiency in Large Language Models is the primary requirement for this role. Candidates should understand how LLMs can be adapted for specific instructions, domains, and application requirements.

Knowledge of natural language processing techniques and language-model fine-tuning strategies is required. Candidates should understand machine learning concepts relevant to model adaptation and be able to evaluate whether changes to training approaches are improving model performance.

Experience with data preprocessing and data augmentation is important because model quality depends on the preparation and suitability of training data. The ability to interpret model performance metrics and use those findings to drive iterative improvements is also expected.

Python knowledge is required as a programming foundation for model development activities. Candidates should be comfortable working with technical workflows involving language models, data, experimentation, and performance analysis.

Preferred Skills

The supplied job description does not identify any specific additional preferred technologies or qualifications. Professionals who can demonstrate practical experience across LLM development, natural language processing, model fine-tuning, data preparation, and model evaluation will be well aligned with the stated requirements.

Education

The position requires 15 years of full-time education. The job description does not specify a particular degree name or specialization, so candidates should ensure their educational background satisfies the stated full-time education requirement.

Experience

A minimum of 3 years of experience in Large Language Models is explicitly required. The job is categorized within a 2-5 years experience range, making experienced LLM developers within the stated range relevant to the opportunity.

Required Technologies and Technical Areas

• Large Language Models (LLMs)
• Natural Language Processing
• Machine Learning
• Python
• Instruction Fine-Tuning
• Domain Adaptation
• Data Preprocessing
• Data Augmentation
• Model Performance Evaluation
• Model Performance Metrics

Soft Skills

The role requires independent execution, analytical thinking, and effective collaboration. Candidates should be able to investigate model behavior, identify technical issues, discuss solutions with team members, and communicate findings clearly.

Active participation in team discussions is important, along with a willingness to document technical work and share knowledge. The position also involves supporting junior colleagues, so mentoring ability and a collaborative attitude are valuable.

A structured approach to experimentation and problem solving is particularly useful because model development often requires repeated evaluation and refinement.

Benefits of Working in this Role

This role offers an opportunity to work directly with Large Language Models and contribute to practical AI development. Professionals can deepen their experience in fine-tuning, domain adaptation, natural language processing, model evaluation, data preparation, and production-oriented AI collaboration.

The opportunity can also help an experienced AI professional strengthen subject matter expertise while working with cross-functional teams and supporting the development of other team members.

Work Mode

The job description identifies the HDC3C - SEZ office in Hyderabad but does not specify a remote or hybrid arrangement. Based on the available information, this listing is classified as onsite.

Location

Hyderabad, India, at the HDC3C - SEZ office.

Who Should Apply

This opportunity is suitable for AI/ML professionals with at least 3 years of experience working with Large Language Models. Candidates should have practical knowledge of LLM fine-tuning, natural language processing, machine learning principles, data preparation, model evaluation, and Python.

It is particularly relevant for professionals who have worked on adapting language models for domain-specific requirements and who can independently analyze model performance and contribute improvements. Candidates should also be comfortable collaborating with technical teams and documenting their work.

Career Growth

The role can support growth toward specialist and subject matter expert positions in LLM development and applied AI. Experience gained in fine-tuning, domain adaptation, performance evaluation, production integration, and technical mentoring can help professionals build a broader profile in the rapidly evolving AI and machine learning field.

Working on practical language model improvement also provides relevant experience for future roles involving AI engineering, LLM development, NLP, model optimization, and applied machine learning.

Application Advice

Keep your resume focused on practical LLM experience rather than listing AI keywords without context. Highlight projects involving model fine-tuning, instruction tuning, domain adaptation, natural language processing, data preprocessing, data augmentation, and model evaluation.

Clearly mention your Python experience and provide examples of how you analyzed model performance or improved language-model behavior. If you have supported production integration, collaborated with cross-functional teams, documented experiments, or mentored junior developers, include those details.

The job specifically requires at least 3 years of LLM experience and 15 years of full-time education, so make both requirements easy for recruiters to verify.