AI/ML Engineer (Only for H4 EAD, L2S, GC/USC)

Job Title: AI/ML Engineer Location: New York Employment Type: Full-Time / W2 About the Role: We are seeking a highly skilled and experienced AI/ML Engineer to design, develop, deploy, and maintain scalable Artificial Intelligence (AI), Machine Learning (ML), and Generative AI solutions for enterprise applications.

Key Responsibilities

• Design, develop, implement, and maintain scalable Artificial Intelligence (AI) and Machine Learning (ML) models to solve complex business problems and support data-driven decision-making.
• Develop machine learning pipelines using Python, Scikit-learn, TensorFlow, PyTorch, Pandas, NumPy, and other AI/ML frameworks.
• Build, train, evaluate, and optimize supervised and unsupervised machine learning models, including classification, regression, clustering, recommendation systems, forecasting, and anomaly detection.
• Design and implement Deep Learning and Neural Network architectures for computer vision, natural language processing, predictive analytics, and other AI-driven applications.
• Develop Generative AI applications using Large Language Models (LLMs) , foundation models, prompt engineering, embeddings, and Retrieval-Augmented Generation (RAG) architectures.
• Build intelligent conversational applications, chatbots, virtual assistants, and AI-powered automation solutions using LLMs, NLP, vector databases, and semantic search.
• Implement RAG pipelines involving document ingestion, text chunking, embedding generation, vector indexing, retrieval strategies, reranking, and context-aware response generation.
• Integrate AI/ML models with enterprise applications through REST APIs, FastAPI, Flask, microservices, and cloud-native application architectures.
• Perform data preprocessing, exploratory data analysis (EDA) , feature engineering, feature selection, data cleansing, and dataset preparation to improve model accuracy and reliability.
• Develop and implement Natural Language Processing (NLP) solutions for text classification, sentiment analysis, named entity recognition (NER), summarization, information extraction, and document intelligence.
• Implement MLOps practices model training, experiment tracking, version control, automated deployment, model monitoring, and machine learning lifecycle management.
• Deploy and manage AI/ML workloads using cloud platforms such as Microsoft Azure, AWS, or Google Cloud Platform (GCP) and their respective AI/ML services.
• Build scalable data processing and model training workflows using Apache Spark, PySpark, Databricks, and distributed computing technologies where required.
• Required Skills & Qualifications: 8+ years of experience in AI Engineering, Machine Learning Engineering, Artificial Intelligence, Software Engineering, or related technical disciplines, with hands-on experience developing and deploying production-grade AI/ML solutions.
• Strong programming proficiency in Python, including libraries such as P andas, NumPy, SciPy, Scikit-learn, and experience writing production-quality, reusable, and maintainable code.
• Strong understanding of Machine Learning algorithms, including Linear Regression, Logistic Regression, Decision Trees, Random Forest, Gradient Boosting, XGBoost, Clustering, Ensemble Learning, and Recommendation Systems.
• Hands-on experience with Deep Learning frameworks such as PyTorch, TensorFlow, and Keras, including neural networks, model training, and optimization.
• Strong knowledge of Generative AI, Large Language Models (LLMs), foundation models, prompt engineering, embeddings, fine-tuning, and LLM application development.
• Familiarity with LLM orchestration frameworks such as LangChain, LangGraph, LlamaIndex, or equivalent technologies.
• Experience with vector databases and vector search technologies such as P inecone, FAISS, Weaviate, Chroma, or Azure AI Search.
• Hands-on experience with MLOps, MLflow, model versioning, experiment tracking, model registry, model serving, CI/CD, and automated ML pipelines.