AI Engineer

Sanas Sets LLC; Arkansas; On-site; USD 90,000 - 110,000; Full time

Job summary

Sanas Sets LLC is seeking an AI Engineer with 1–3 years of experience to develop, test, and deploy ML solutions. The role involves building data pipelines, evaluating models, and applying Generative AI and LLM techniques across projects.

You will collaborate with software engineers and data teams to ship reliable AI-powered features. The ideal candidate has hands-on Python experience, familiarity with PyTorch/TensorFlow, and knowledge of data processing, model evaluation, and cloud deployment

Qualifications

• 1–3 years of experience in AI/ML or related field.
• Strong programming skills in Python.
• Experience with ML frameworks (PyTorch, TensorFlow, Scikit-learn).
• Familiarity with NLP, GenAI, LLMs, or CV.

Responsibilities

• Develop, train, test, and optimize ML models in Python.
• Prepare and analyze datasets for AI/ML applications.
• Implement ML algorithms for classification, regression, and clustering.
• Support deployment of AI applications into production environments.
• Collaborate with cross-functional teams and document processes.

Skills

Python programming

ML concepts

NLP/GenAI/LLMs

Data preprocessing

SQL

REST APIs

Cloud platforms

Docker

Git

Model evaluation

Tools

PyTorch

TensorFlow

Scikit-learn

FastAPI/Flask/REST

CI/CD

Hugging Face Transformers

Vector databases

Job description

Job Summary

We are seeking an AI Engineer with 1 3 years of experience to support the development, implementation, testing, and deployment of AI and machine learning solutions. The ideal candidate will have hands-on experience with Python, machine learning, deep learning, data processing, and AI/ML frameworks and an interest in emerging technologies such as Generative AI and Large Language Models (LLMs).

The AI Engineer will work with cross-functional teams to build and improve AI models, develop data-driven solutions, evaluate model performance, and assist with deploying AI applications into production environments.

Key Responsibilities

• Develop, train, test, and optimize machine learning and deep learning models using Python.
• Prepare, clean, transform, and analyze structured and unstructured datasets for AI/ML applications.
• Implement machine learning algorithms for classification, regression, clustering, and predictive analytics.
• Work with PyTorch, TensorFlow, Scikit-learn, or similar machine learning frameworks.
• Support development of Generative AI and LLM-based applications, including prompt engineering and model evaluation.
• Build and maintain RAG (Retrieval-Augmented Generation) pipelines and AI-powered applications when required.
• Work with APIs, databases, and data-processing pipelines to integrate AI models into applications.
• Develop and maintain AI/ML services using technologies such as FastAPI, Flask, or REST APIs.
• Evaluate model accuracy, performance, scalability, and reliability and recommend improvements.
• Assist with model deployment, monitoring, versioning, and maintenance in development and production environments.
• Work with cloud platforms such as AWS, Azure, or Google Cloud for AI/ML workloads.
• Use Git/GitHub, Docker, and CI/CD tools to support development and deployment workflows.
• Collaborate with software engineers, data scientists, data engineers, and product teams.
• Document models, experiments, data pipelines, APIs, and technical processes.
• Stay current with developments in Artificial Intelligence, Machine Learning, Generative AI, LLMs, and MLOps.

Required Skills

• 1 3 years of experience in AI, Machine Learning, Data Science, or a related field.
• Strong programming skills in Python.
• Knowledge of Machine Learning and Deep Learning concepts.
• Experience with PyTorch, TensorFlow, Scikit-learn, or equivalent frameworks.
• Understanding of NLP, Generative AI, LLMs, or Computer Vision.
• Knowledge of data preprocessing, feature engineering, model training, and model evaluation.
• Experience with SQL and working with databases.
• Familiarity with REST APIs and Git/GitHub.
• Understanding of cloud platforms such as AWS, Azure, or GCP.
• Familiarity with Docker and MLOps concepts is a plus.
• Strong analytical, problem-solving, and communication skills.

Preferred AI/GenAI Skills

• Large Language Models (LLMs)
• Generative AI
• Prompt Engineering
• RAG
• LangChain or LlamaIndex
• Hugging Face Transformers
• Vector Databases such as Pinecone, FAISS, Weaviate, or Milvus
• AI model deployment and monitoring
• MLOps