Gen AI Developer-6

Realign Llc; Richardson (TX); On-site; USD 120,000 - 180,000; Full time

Job summary

Realign Llc in Richardson, TX is seeking a full-time AI engineering expert to design, fine-tune, and deploy generative AI models across applications. You will work with Llama, GPT, and diffusion models, and build robust data pipelines for model training and inference.

You will optimize LLMs for natural language understanding, summarization, and conversational AI, and ensure scalable, cost-efficient deployments on AWS, Azure, and GCP.

Qualifications

• Experience in machine learning, data science, or related fields.
• Hands-on experience with generative models (GANs, VAEs, diffusion models) and LLMs.
• Proficiency with ML frameworks TensorFlow, PyTorch, or JAX.
• Familiarity with cloud environments (AWS Sagemaker, Azure ML, or GCP).
• Strong Python programming skills (preferred) or similar languages.
• Experience with libraries such as Hugging Face, LangChain, or NVIDIA BioNeMo.
• Knowledge of Docker, Kubernetes, and CI/CD pipelines for deployment.
• Understanding of NLP, computer vision, or multimodal AI techniques.
• Strong problem-solving skills and a passion for AI-driven innovation.
• Experience with Retrieval-Augmented Generation (RAG) techniques and vector databases (Pinecone, Weaviate, Milvus).

Responsibilities

• Design, fine-tune, and deploy generative AI models (e.g., Llama, GPT, Stable Diffusion) for various applications.
• Train and optimize large language models (LLMs) for tasks such as natural language understanding, summarization, and conversational AI.
• Develop and maintain robust data pipelines for model training and inference.
• Clean, preprocess, and manage large-scale datasets to support AI projects.
• Implement ML models in production environments using TensorFlow, PyTorch, or Hugging Face.
• Optimize models for performance, scalability, and cost-efficiency on cloud platforms (AWS, Azure, GCP).
• Work with product managers, data engineers, and software developers to align AI solutions with business objectives.
• Stay updated with the latest research and advancements in Gen AI and ML.
• Monitor deployed models for performance and accuracy; implement retraining and versioning strategies.
• Ensure systems meet ethical, privacy, and compliance standards

Skills

Machine learning & data science

Python programming

NLP / CV / multimodal AI understanding

Problem solving

RAG techniques

Tools

TensorFlow

PyTorch

JAX

AWS Sagemaker

Azure ML

GCP AI Platform

Hugging Face

LangChain

NVIDIA BioNeMo

Docker

Kubernetes

CI/CD

Pinecone

Weaviate

Milvus

Job description

Full Time

Job Description

Must Have Technical/Functional Skills

Experience

• Experience in machine learning, data science, or related fields.
• Hands-on experience with generative models (e.g., GANs, VAEs, diffusion models) and LLMs.
• Experience with ML frameworks (e.g., TensorFlow, PyTorch, JAX).
• Familiarity with cloud environments (AWS Sagemaker, Azure ML, or GCP AI Platform).
• Strong programming skills in Python (preferred) or similar languages.
• Proficiency in using libraries like Hugging Face, LangChain, or NVIDIA BioNeMo.
• Knowledge of Docker, Kubernetes, and CI/CD pipelines for deployment.
• Understanding of NLP, computer vision, or multimodal AI techniques.
• Strong problem-solving skills and a passion for AI-driven innovation.
• Experience with Retrieval-Augmented Generation (RAG) techniques and vector databases (e.g., Pinecone, Weaviate, Milvus).

Responsibilities

Model Development and Deployment

• Design, fine-tune, and deploy generative AI models (e.g., Llama, GPT, Stable Diffusion) for various applications.
• Train and optimize large language models (LLMs) for tasks such as natural language understanding, summarization, and conversational AI.
• Develop and maintain robust data pipelines for model training and inference.
• Clean, preprocess, and manage large-scale datasets to support AI projects.

3. Integration and Scalability

• Implement ML models in production environments using tools like TensorFlow, PyTorch, or Hugging Face.
• Optimize models for performance, scalability, and cost-efficiency on cloud platforms (AWS, Azure, GCP).

4. Collaboration and Innovation

• Work with product managers, data engineers, and software developers to align AI solutions with business objectives.
• Stay updated with the latest research and advancements in Gen AI and ML.

5. System Monitoring and Maintenance

• Monitor deployed models for performance and accuracy; implement retraining and versioning strategies.
• Ensure systems meet ethical, privacy, and compliance standards