LLM Fine Tuning Specialist

Published on CazVidat Employer

We are seeking a highly motivated LLM Fine Tuning Specialist to join our team on a contract basis in Boston, Massachusetts. Our company is at the forefront of d

Verified by CazVid12 months agoOpen until: Nov 29, 2026

Salary

$100,000 per year

Location

Boston, Massachusetts, United States

Employment type

Contract

Workplace

Not provided

LLM Fine Tuning Specialist

$100,000 per year

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Job description

We are seeking a highly motivated LLM Fine Tuning Specialist to join our team on a contract basis in Boston, Massachusetts. Our company is at the forefront of developing cutting-edge AI models and technologies. As a pivotal member of our organization, you will contribute to the advancement of machine learning models in a collaborative and innovative work environment. This role will significantly impact our ability to deliver high-quality output that meets client needs and drives our mission forward. Key Responsibilities Develop and implement fine-tuning strategies for large language models (LLMs) to enhance their performance. Analyzing training data and refining datasets to optimize model accuracy. Collaborating with data scientists and machine learning engineers to integrate fine-tuned models into existing systems. Conducting experiments and evaluations of model performance using standard metrics. Documenting methodologies, processes, and results to ensure reproducibility and transparency. Staying updated on the latest developments in LLM technologies and best practices. Participating in team meetings to report on progress, share insights, and strategize on upcoming projects. Required and Preferred Qualifications Master's Degree in Computer Science or a related field. Proven experience working with large language models (LLM) in a professional setting. Strong programming skills, particularly in Python and relevant machine learning frameworks (e.g., TensorFlow, PyTorch). Familiarity with model evaluation techniques and performance metrics. Experience with cloud-based machine learning environments and tools. 3-5 years of relevant experience in AI/ML fields preferred. In addition to a competitive contract period, we offer growth opportunities where you'll expand your expertise in advanced machine learning techniques. Our company culture fosters innovation, teamwork, and continuous learning. We embrace a modern workplace environment that includes flexible working hours, and a strong commitment to professional development, ensuring every team member has access to resources for their career growth. Common tools utilized in our operations include Git for version control, Jupyter Notebooks for exploratory data analysis, and cloud computing platforms such as AWS or Azure. The LLM Fine Tuning Specialist will be part of a dynamic team structure, reporting directly to the Lead Data Scientist while collaborating closely with software engineers and other cross-functional teams to support our overarching projects and objectives. This role provides an enticing opportunity to engage in the evolving field of artificial intelligence while making tangible contributions to exciting new projects.

Frequently asked questions

  • Is this position remote or on-site?

    This role requires on-site presence in Boston, Massachusetts, and remote work is not eligible.

  • What is the salary for this contract role?

    The contract position offers a competitive annual pay of USD 100,000 per year.

  • What qualifications do I need to apply?

    You need a Master's Degree in Computer Science or a related field, proven experience with large language models, strong programming skills in Python and ML frameworks like TensorFlow or PyTorch, and familiarity with model evaluation techniques.

  • What kind of experience is preferred for this role?

    3-5 years of relevant AI/ML experience is preferred, along with experience in cloud-based machine learning environments and tools.

  • What will my main responsibilities be?

    You will develop and implement fine-tuning strategies for LLMs, analyze and refine training datasets, collaborate with data scientists and engineers, conduct experiments, evaluate model performance, and document methodologies.

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