Job Title: Senior AI/ML Engineer

Location: Onsite
Employment Type: W2 Only
Experience Required: 15+ Years

Job Summary

We are seeking a highly experienced Senior AI/ML Engineer to design, develop, and deploy advanced Artificial Intelligence and Machine Learning solutions. The ideal candidate will have extensive experience in building scalable ML models, implementing AI-driven applications, and working with large-scale data environments. This role requires strong expertise in machine learning algorithms, deep learning frameworks, cloud platforms, and MLOps practices.

Required Qualifications

• 15+ years of overall IT experience with 5+ years focused on AI/ML engineering.
• Bachelor''s or Master''s degree in Computer Science, Data Science, Artificial Intelligence, or a related field.
• Strong experience with Python and ML libraries such as TensorFlow, PyTorch, Scikit-learn, Keras, and XGBoost.
• Experience with Generative AI, Large Language Models (LLMs), Prompt Engineering, RAG, Vector Databases, and AI Agents.
• Hands-on experience with OpenAI, Anthropic, Gemini, or similar AI platforms.
• Strong knowledge of Machine Learning, Deep Learning, NLP, Computer Vision, and Predictive Analytics.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
• Expertise in MLOps tools including MLflow, Kubeflow, SageMaker, Vertex AI, or Azure ML.
• Experience with data engineering technologies including Spark, Databricks, Hadoop, and SQL/NoSQL databases.
• Strong understanding of model deployment, monitoring, optimization, and governance.
• Excellent communication and stakeholder management skills.

Responsibilities

• Design, develop, and deploy machine learning and AI solutions for enterprise applications.
• Build and optimize predictive models, recommendation systems, NLP solutions, and Generative AI applications.
• Develop AI-powered chatbots, virtual assistants, and intelligent automation solutions.
• Implement RAG architectures using vector databases and LLM frameworks.
• Collaborate with data engineers, architects, and business stakeholders to deliver AI-driven solutions.
• Establish MLOps pipelines for model training, deployment, monitoring, and lifecycle management.
• Ensure AI solutions meet performance, scalability, security, and compliance requirements.
• Stay current with emerging AI/ML technologies and industry best practices.

Preferred Certifications

• AWS Certified Machine Learning – Specialty
• Microsoft Azure AI Engineer Associate
• Google Professional Machine Learning Engineer
• Databricks Certified Machine Learning Professional
• TensorFlow Developer Certification