Position: Senior AI/ML Engineer

Raas Infotek LTD; Atlanta (GA); On-site; USD 120,000 - 160,000; Full time

Job summary

Raas Infotek LTD seeks a skilled AI/ML engineer to design, develop, and deploy scalable AI/ML solutions for enterprise applications. You will build end-to-end pipelines, train and evaluate models, and optimize performance for production environments.

You will collaborate with data engineering and software teams, leverage cloud services (AWS/Azure/GCP), and apply MLOps practices (Docker, Kubernetes, CI/CD) to deliver impactful AI-driven outcomes.

Qualifications

• Experience designing, developing, and deploying scalable AI/ML solutions.
• Proficient in Python and modern ML libraries.
• Hands-on with NLP, LLMs, and generative AI.
• Experience building and evaluating ML models for production.

Responsibilities

• Design, develop, and deploy scalable AI/ML solutions for enterprise applications.
• Build and maintain ML pipelines, model training, evaluation, deployment, and monitoring.
• Collaborate with data engineering to prepare and analyze large datasets.
• Optimize models for scalability, accuracy, performance in production environments.
• Work with cloud platforms (AWS/Azure/GCP) and MLOps tools (Docker, Kubernetes, CI/CD).
• Partner with business and engineering teams to deliver AI-driven solutions.

Skills

Python

Machine Learning

Deep Learning

Generative AI

NLP

LLMs

Prompt engineering

Embeddings

Vector databases

MLOps

Docker

Kubernetes

CI/CD

Model versioning

Cloud platforms

Tools

TensorFlow

PyTorch

Scikit-learn

Pandas

NumPy

Job description

• Design, develop, and deploy scalable AI/ML solutions for enterprise applications.
• Strong experience with Python, Machine Learning, Deep Learning, and Generative AI.
• Hands-on experience with TensorFlow, PyTorch, Scikit-learn, Pandas, and NumPy.
• Experience building and deploying NLP, LLM, recommendation, classification, and predictive models.
• Strong knowledge of Generative AI, LLMs, RAG, prompt engineering, embeddings, and vector databases.
• Experience with AWS, Azure, or Google Cloud Platform cloud platforms and AI/ML services.
• Build and maintain ML pipelines, model training, evaluation, deployment, and monitoring.
• Experience with MLOps, Docker, Kubernetes, CI/CD, and model versioning.
• Work with data engineering teams to prepare, process, and analyze large datasets.
• Optimize models for scalability, accuracy, performance, and production environments.
• Collaborate with business, data, and engineering teams to deliver AI-driven solutions.
• Strong analytical, problem-solving, and communication skills.