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Ml Model Fine Tuning Jobs (NOW HIRING)

TSMC

Senior AI Model Fine-Tuning Engineer

Phoenix, AZ · On-site

$103K - $142K/yr

As a Senior AI Model Fine-Tuning Engineer, you will adjust the behavior and functional abilities of AI models to enhance their adaptability and intelligence, utilizing advanced techniques like prompt ...

TSMC

Senior AI Model Fine-Tuning Engineer

Phoenix, AZ

$128K - $176K/yr

Senior AI Model Fine-Tuning Engineer A job at TSMC Arizona offers an opportunity to work at the most advanced semiconductor fab in the United States. TSMC Arizona's first fab will operate it ...

TSMC

Senior AI Model Fine-Tuning Engineer

Phoenix, AZ · On-site

$128K - $176K/yr

Senior AI Model Fine-Tuning Engineer A job at TSMC Arizona offers an opportunity to work at the most advanced semiconductor fab in the United States. TSMC Arizona's first fab will operate it ...

TMS

AI/ ML Engineer

New York, NY · Remote

$60 - $62/hr

Role: AI/ ML Engineer Duration: 6 months contract Location: US/ Canada- Remote Minimum exp ... The ideal candidate will have hands-on experience with prompt engineering, model fine-tuning, and ...

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Ml Model Fine Tuning information

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How much do ml model fine tuning jobs pay per hour?

As of Jun 13, 2026, the average hourly pay for ml model fine tuning in the United States is $69.33, according to ZipRecruiter salary data. Most workers in this role earn between $56.73 and $76.92 per hour, depending on experience, location, and employer.

What is the difference between Ml Model Fine Tuning vs Data Scientist?

AspectMl Model Fine TuningData Scientist
CredentialsKnowledge of machine learning frameworks, programming skillsDegree in data science, statistics, or related fields
Work EnvironmentFocus on model optimization, coding, and experimentationData analysis, modeling, and interpretation
Industry UsageAI/ML development teams, tech companiesResearch, analytics, business intelligence

While Ml Model Fine Tuning involves adjusting pre-trained models to improve performance, Data Scientists analyze data, develop models, and interpret results. Fine tuning is a specialized task within the broader scope of a Data Scientist's role, often requiring similar technical skills but focusing more on model optimization.

What are some common challenges faced when fine-tuning machine learning models in a production environment?

One common challenge when fine-tuning ML models in production is ensuring that the updated models generalize well to new, unseen data without overfitting to recent trends or noise. Additionally, coordinating with data engineers and software developers is crucial to maintain data pipelines and model deployment workflows. Managing computational resources and keeping track of model versions for reproducibility can also be complex, especially in fast-paced or large-scale environments. Regular communication with stakeholders is important to align model updates with business objectives and to ensure the smooth integration of improvements.

What is ML model fine-tuning?

ML model fine-tuning is the process of taking a pre-trained machine learning model and making small adjustments to its parameters using new data relevant to your specific task. This approach allows you to leverage the general knowledge the model has already learned, while adapting it to perform better on your particular dataset or problem. Fine-tuning is common in fields like natural language processing and computer vision, as it saves time and resources compared to training a model from scratch. The process typically involves retraining the last few layers of the model or using a lower learning rate for the entire model.

What are the key skills and qualifications needed to thrive as an ML Model Fine Tuning Specialist, and why are they important?

To thrive as an ML Model Fine Tuning Specialist, you need a solid background in machine learning, statistics, programming (often Python), and experience with model training and evaluation. Familiarity with frameworks such as TensorFlow, PyTorch, and tools like Hugging Face Transformers, along with experience in managing GPUs and cloud platforms, is typically required. Strong problem-solving skills, attention to detail, and effective communication help you understand project requirements and collaborate with data scientists and engineers. These skills are crucial for optimizing model performance, ensuring accurate results, and delivering robust AI solutions tailored to specific business needs.
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Ml Model Fine Tuning jobs near you
Infographic showing various Ml Model Fine Tuning job openings in the United States as of June 2026, with employment types broken down into 100% Full Time. Highlights an 33% In-person, and 67% Remote job distribution, with an average salary of $144,212 per year, or $69.3 per hour.

Senior AI Model Fine-Tuning Engineer

TSMC

Phoenix, AZ • On-site

$103K - $142K/yr

Full-time

Posted 4 days ago

TSMC rating

8.2

Company rating: 8.2 out of 10

Based on 19 frontline employees who took The Breakroom Quiz

37th of 139 rated electronics manufacturers

Job description

Job Summary:
TSMC Arizona offers an opportunity to work at the most advanced semiconductor fab in the United States. As a Senior AI Model Fine-Tuning Engineer, you will adjust the behavior and functional abilities of AI models to enhance their adaptability and intelligence, utilizing advanced techniques like prompt engineering and RLHF.
Responsibilities:
• Lead the fine-tuning process for large pre-trained models, focusing on making models behave appropriately in different contexts (e.g., following instructions, answering questions, or performing tasks).
• Design and implement prompt engineering strategies to help the model produce more accurate, relevant, and coherent outputs.
• Apply Reinforcement Learning from Human Feedback (RLHF) and other behavioral fine-tuning methods to improve the model's alignment with user needs and ethical standards.
• Collaborate with data teams to integrate relevant data and continuously improve model behavior.
• Conduct model evaluations using various performance metrics (accuracy, bias detection, user feedback) to identify areas for improvement.
• Iterate and experiment with different fine-tuning methods to achieve optimal performance for specific use cases.
• Monitor model drift and ensure that models remain consistent, reliable, and safe over time.
Qualifications:
Required:
• Bachelor's degree in Computer Science, Data Science, or a related field.
• 5+ years of experience working on fine-tuning large-scale models such as GPT, T5, or BERT, with a strong focus on behavior and functionality.
• Expertise in advanced tuning methods such as RLHF, prompt engineering, and zero-shot learning.
• Experience with popular transformer architectures and frameworks like Hugging Face, TensorFlow, or PyTorch.
• Deep understanding of LLM behaviors, including instruction-following, task completion, and ethical considerations in output.
• Proficiency in Python and experience with libraries for model fine-tuning (e.g., Transformers, DeepSpeed).
• Experience in evaluating model performance, including using metrics like BLEU, ROUGE, perplexity, and custom evaluation frameworks.
• Candidates must be willing and able to work on-site at our Phoenix Arizona facility.
• Communication
• Computer proficiency
• Presentation skills
• Listening
• Teamwork
Preferred:
• Experience with ethical AI and safety considerations, such as minimizing bias and handling adversarial inputs.
• Experience with model deployment and real-time experimentation (A/B testing).
Company:
Established in 1987, TSMC is the world's first dedicated semiconductor foundry. Founded in 1987, the company is headquartered in Hsinchu, TWN, with a team of 10001+ employees. The company is currently Late Stage.

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