Gen AI Developer

Section

Details

Job Title

Gen AI Developer

Job Type

Full Time

Client Location

Long Beach, CA

Work Arrangement

Onsite

Duration

Full Time

Pay Rate / Salary

$120-$150k/yr.

Job Summary

• A Gen AI Developer designs, develops, and deploys Generative AI solutions using large language models (LLMs), machine learning, NLP, and modern AI frameworks.
• The role involves building RAG-based applications, AI agents, prompt engineering workflows, vector search solutions, and LLM-powered applications that integrate with enterprise data and business systems.
• The developer collaborates with data scientists, software engineers, product teams, and business stakeholders to deliver scalable, secure, and production-ready AI solutions.

Key Responsibilities

• Bachelor's or master's degree in computer science, data science or equivalent
• Develop and implement generative AI models using frameworks like TensorFlow and PyTorch.
• Build and optimize RAG (Retrieval-Augmented Generation) pipelines.
• Work on NLP tasks such as text classification, summarization, and conversational AI.
• Perform data pre-processing, cleaning, and feature engineering using Python libraries (NumPy, Pandas).
• Fine-tune and optimize transformer-based models and LLMs for specific use cases.
• Evaluate model performance using RAG and NLP evaluation metrics.
• Develop and integrate machine learning models into applications.
• Apply autonomous decision-making logic in AI-driven workflows where needed.

Required Qualifications

• Experience in executing projects in Agile Framework
• Proven experience in machine learning and deep learning frameworks (e.g., TensorFlow, PyTorch).
• Strong programming skills in Python and familiarity with libraries such as NumPy, Pandas, and Scikit-learn.
• Experience with generative models (e.g., GANs, VAEs, Transformers) and natural language processing.
• Proficiency in RAG (Retrieval-Augmented Generation) techniques.
• Strong understanding of natural language processing (NLP). Experience with data pre-processing and model fine-tuning.
• Familiarity with evaluation metrics for RAG systems.
• Knowledge of transformer architectures and training techniques.
• Awareness of ethical considerations and bias mitigation strategies.
• Understanding of autonomous decision-making algorithms.
• Proficiency in programming language Python.
• Strong analytical and problem-solving skills.