Gen AI Developer-6

Realign Llc; Everett (WA); On-site; USD 140,000 - 200,000; Full time

Job summary

Realign Llc in Everett, WA seeks a full-time AI/ML engineer to design, fine-tune, and deploy generative models (LLMs, diffusion, GANs) for diverse applications. You will build robust data pipelines and train models for production use.

Collaborate with product managers and data engineers to align AI solutions with business goals. Proficient Python and ML frameworks (TensorFlow, PyTorch) plus Hugging Face, LangChain, Docker, Kubernetes, and vector databases are required.

Qualifications

• Experience in ML, data science, or related fields.
• Hands-on 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 programming skills in Python (preferred) or similar languages.
• Proficiency with 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

• 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 tools like 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

Natural Language Processing

Python

RAG

Vector Databases

CI/CD for ML

Cloud Deployment

Tools

TensorFlow

PyTorch

JAX

Hugging Face

LangChain

NVIDIA BioNeMo

Docker

Kubernetes

Job description

Everett, Washington 98201 Posted October 19th, 2026

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