Gen AI Developer-6

Realign Llc

Plano (TX)

On-site

USD 120,000 - 190,000

Full time

23 hours ago
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Job summary

Realign Llc in Plano, TX seeks a hands-on machine learning engineer to design, train, and deploy generative AI models including LLMs and diffusion systems. You will build robust data pipelines, optimize models for cloud deployment, and collaborate with product teams to translate AI research into practical solutions.

The role requires strong Python skills, experience with TensorFlow/PyTorch, Hugging Face, and vector databases, plus familiarity with Docker, Kubernetes, and CI/CD for scalable

Qualifications

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

Responsibilities

  • Design, fine-tune, and deploy generative AI models for various applications.
  • Train and optimize large language models for NLU, summarization, and conversational AI.
  • Develop and maintain robust data pipelines for training and inference.
  • Clean, preprocess, and manage large-scale datasets.
  • Implement ML models in production using TensorFlow, PyTorch, or Hugging Face.
  • Optimize models for performance, scalability, and cloud costs.

Skills

Generative models
Python
TensorFlow
PyTorch
JAX
Cloud platforms
Docker
Kubernetes
CI/CD
Hugging Face
LangChain
RAG
Vector databases
NLP/vision/multimodal
Data pipelines

Education

Tools

TensorFlow
PyTorch
JAX
Docker
Kubernetes
Hugging Face

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
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