NLP Model Developer

2 days ago


Pune, Maharashtra, India JetSynthesys Full time

**Job Title:** NLP Model Developer

We are looking for an experienced NLP Model Developer to join our team at JetSynthesys in Pune. As a key member of our technology team, you will be responsible for developing and deploying natural language processing (NLP) solutions using large language models (LLMs).

**Salary:** ₹25,00,000 - ₹35,00,000 per annum

**Job Description:**

The ideal candidate will have a strong background in NLP, machine learning, and artificial intelligence with hands-on experience in deploying and fine-tuning LLMs. Responsibilities include:

• Developing and optimizing NLP models using LLMs to solve complex problems.

• Collaborating with data scientists and software engineers to integrate NLP capabilities into the product.

• Developing scalable machine learning pipelines for training, testing, and deploying NLP models.

• Analyzing and improving the performance of models by experimenting with different architectures, hyperparameters, and datasets.

• Staying updated with the latest advancements in NLP, machine learning, and AI technologies and applying them to enhance model performance.

• Troubleshooting and resolving issues related to model accuracy, latency, and scalability.

Education Requirements:

• Bachelor's or master's degree in computer science, engineering, or a related field.

• Preferred: Publications or contributions to research papers in the field of NLP or machine learning.

• Experience in working on multilingual models or domain-specific NLP models.

• Strong experience with NLP, deep learning, and machine learning frameworks like TensorFlow, PyTorch, Hugging Face, etc.

• Expertise in working with large pre-trained models such as GPT, BERT, T5, etc.

• Proficient in Python and libraries such as NumPy, pandas, and Scikit-learn.

• Familiarity with distributed systems and cloud platforms like AWS, Azure, or Google Cloud for model deployment.

• Experience in fine-tuning, training, and deploying models in a production environment.

• Knowledge of data engineering practices to manage large-scale data pipelines for model training and inference.

• Strong analytical and problem-solving skills, with the ability to work in a fast-paced environment.



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