Job Title: AI/ML Engineer

Location: Phoenix, AZ (Onsite)
Employment Type: W2 Contract
Work Arrangement: 100% Onsite
Experience: 8–10+ Years

Job Summary

We are looking for an experienced AI/ML Engineer with strong hands-on experience in developing, deploying, and maintaining scalable Artificial Intelligence and Machine Learning solutions. The ideal candidate should have expertise in Python, machine learning algorithms, deep learning, Generative AI, Large Language Models (LLMs), and cloud-based AI platforms.

The candidate will work closely with data scientists, software engineers, and business stakeholders to design and implement intelligent applications, predictive models, and AI-powered solutions that solve complex business problems.

Key Responsibilities

• Design, develop, train, and deploy Machine Learning and Deep Learning models for real-world business applications.

• Build and optimize predictive models using supervised, unsupervised, and reinforcement learning techniques.

• Develop scalable AI/ML solutions using Python and frameworks such as TensorFlow, PyTorch, and Scikit-learn.

• Design and implement Generative AI applications using Large Language Models (LLMs).

• Develop Retrieval-Augmented Generation (RAG) pipelines using vector databases and embedding models.

• Work with LLM frameworks such as LangChain, LlamaIndex, and other AI orchestration frameworks.

• Implement prompt engineering, model fine-tuning, and evaluation techniques to improve LLM performance.

• Integrate AI/ML models with enterprise applications through REST APIs and microservices.

• Build and maintain data preprocessing, feature engineering, and model evaluation pipelines.

• Implement MLOps practices for model deployment, monitoring, versioning, and continuous improvement.

• Work with cloud-based AI/ML services across AWS, Azure, or Google Cloud Platform.

• Collaborate with cross-functional teams to translate business requirements into scalable AI solutions.

• Ensure model performance, scalability, security, reliability, and responsible AI practices.

Required Technical Skills

• Programming: Strong hands-on experience with Python, SQL, and object-oriented programming.

• Machine Learning: Supervised Learning, Unsupervised Learning, Regression, Classification, Clustering, and Predictive Modeling.

• Deep Learning: TensorFlow, PyTorch, Keras, Neural Networks, and NLP.

• Generative AI: LLMs, Generative AI, Prompt Engineering, RAG, Embeddings, and Fine-Tuning.

• AI Frameworks: LangChain, LlamaIndex, Hugging Face Transformers, and Scikit-learn.

• Vector Databases: Pinecone, FAISS, ChromaDB, Weaviate, or Azure AI Search.

• Cloud Platforms: AWS SageMaker, Azure Machine Learning, or Google Vertex AI.

• MLOps: MLflow, Kubeflow, Docker, Kubernetes, CI/CD, and model monitoring.

• API Development: FastAPI, Flask, REST APIs, and Microservices.

• Data Engineering: Pandas, NumPy, Spark, ETL/ELT pipelines, and data preprocessing.

Preferred / Nice-to-Have Skills

• Experience with AI Agents and Agentic AI architectures.

• Hands-on experience with OpenAI, Azure OpenAI, AWS Bedrock, or Google Gemini.

• Knowledge of Multi-Agent Systems and AI orchestration.

• Experience with model quantization, optimization, and inference acceleration.

• Familiarity with Responsible AI, model governance, and explainable AI.

• Experience working with large-scale enterprise AI applications.