AI/ML Engineer Jobs in US | Artificial Intelligence & Machine Learning Engineer
We are looking for an experienced AI/ML Engineer to build intelligent, scalable, and production-ready Artificial Intelligence and Machine Learning solutions. The ideal candidate will have expertise in machine learning, deep learning, generative AI, large language models (LLMs), computer vision, natural language processing (NLP), and AI automation.
As an AI/ML Engineer, you will design end-to-end AI systems, develop intelligent automation workflows, build AI-powered applications, and integrate enterprise AI solutions into existing business platforms. This role is ideal for professionals looking for AI/ML Engineer Jobs in US (Remote) with exposure to modern AI technologies, cloud AI platforms, and production-scale machine learning deployments.
Key Responsibilities
- Develop and manage robust AI and Machine Learning applications, ensuring they are scalable, efficient, and optimized for production environments.
- Build intelligent AI applications using Machine Learning, Deep Learning, and Generative AI technologies.
- Develop production-ready AI models for prediction, classification, recommendation, and automation.
- Design AI pipelines for data ingestion, preprocessing, model training, evaluation, deployment, and monitoring.
- Build and optimize Large Language Model (LLM) applications using prompt engineering, Retrieval-Augmented Generation (RAG), and AI agent frameworks.
- Develop Natural Language Processing (NLP) solutions for text classification, entity extraction, summarization, sentiment analysis, and conversational AI.
- Build Computer Vision solutions including OCR, image recognition, document processing, object detection, and image classification.
- Develop AI-powered automation workflows using intelligent agents and enterprise AI orchestration frameworks.
- Build efficient Python applications for data processing, AI model integration, and workflow automation.
- Develop optimized SQL queries for data extraction, transformation, and analytics.
- Integrate AI services with enterprise applications through REST APIs and microservices.
- Monitor model performance, improve inference efficiency, and retrain models to maintain accuracy.
- Apply MLOps reliable and valuable processes and procedures for model versioning, deployment, monitoring, and lifecycle management.
- Collaborate with software developers, cloud engineers, data engineers, business analysts, and product teams to deliver AI-driven business solutions.
- Document AI architecture, technical designs, deployment procedures, and model governance standards.
- Stay updated with emerging advancements in Artificial Intelligence, Machine Learning, Generative AI, multimodal AI, and autonomous AI systems.
Required Skills
- Strong experience as an AI/ML Engineer in enterprise or production environments.
- Expertise in Machine Learning, Deep Learning, and Artificial Intelligence concepts.
- Practical experience with Large Language Models (LLMs) and Generative AI applications.
- Strong Python programming skills for AI model development.
- Experience writing optimized SQL queries and handling structured datasets.
- Knowledge of Computer Vision, OCR, and image processing techniques.
- Strong understanding of Natural Language Processing (NLP) and text analytics.
- Experience building REST APIs and integrating AI services with enterprise applications.
- Familiarity with MLOps, model deployment, monitoring, and automation.
- Strong analytical thinking, debugging, and problem-solving skills.
- Excellent communication and collaboration abilities.
Technology Requirements
Programming Languages
- Python
- SQL
- Java (Preferred)
- JavaScript (Preferred)
Machine Learning & Deep Learning
- Scikit-learn
- TensorFlow
- PyTorch
- Keras
- XGBoost
- LightGBM
Generative AI & Large Language Models
- OpenAI GPT
- Claude
- Gemini
- Llama
- Mistral
- Hugging Face Transformers
- LangChain
- LlamaIndex
- Semantic Kernel
- Prompt Engineering
- Retrieval-Augmented Generation (RAG)
AI Agents & Automation
- LangGraph
- CrewAI
- AutoGen
- AI Agent Frameworks
- Workflow Automation
- Intelligent Process Automation
Cloud Platforms
- Microsoft Azure AI
- Azure OpenAI
- AWS AI Services
- Amazon SageMaker
- Google Vertex AI
Data Engineering
- Pandas
- NumPy
- Apache Spark
- ETL Pipelines
- Data Warehousing
Databases
- SQL Server
- PostgreSQL
- MySQL
- MongoDB
- Vector Databases (Pinecone, FAISS, ChromaDB)
DevOps & MLOps
- MLflow
- Docker
- Kubernetes
- Git
- GitHub
- GitLab
- CI/CD Pipelines
Educational Qualification
- Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, Information Technology, Electronics, or a related field.
- Master’s degree in AI, Machine Learning, Data Science, or Computer Science is preferred.
Preferred Certifications
- Microsoft Azure AI Engineer Associate
- Microsoft Azure AI Fundamentals
- AWS Certified Machine Learning – Specialty
- Google Professional Machine Learning Engineer
- TensorFlow Developer Certificate
- Databricks Machine Learning Certification