AI / ML Engineer

Position Overview

The need is for several strong AI/ML engineers. With experience spanning POC, model design to deployment in a large enterprise environment. GenAI, AWS, strong Python coding skills.

Key Responsibilities

• Model Deployment & Maintenance: Focus on deploying, monitoring, and maintaining GenAI models in production, ensuring they function reliably in real-world settings.
• Data Engineering: Build and maintain efficient data pipelines and storage solutions that support model operations.
• Infrastructure Management: Utilize cloud platforms (AWS, Azure, GCP) for model deployment, containerization (Docker), orchestration (Kubernetes), and infrastructure as code (Terraform/CloudFormation).
• DevOps & Automation: Develop CI/CD pipelines, manage version control (Git), and automate deployment processes for seamless operational efficiency.
• Security & Monitoring: Implement secure coding practices, authentication, authorization, and set up robust monitoring and alerting systems for both infrastructure and model performance.
• Generative AI Expertise: Deep understanding of LLMs, GenAI architectures, frameworks like Hugging Face, prompt engineering, and specialized infrastructure for GenAI workloads.
• Advanced Techniques: Apply advanced GenAI techniques like Retrieval-Augmented Generation (RAG), hallucination monitoring, and human-in-the-loop systems.
• Agent Development: Design and develop agent and multi-agent systems using frameworks like LangChain, enabling them to interact with external APIs and tools efficiently.
• Cost Optimization: Implement strategies to manage and reduce the operational costs associated with GenAI deployments.

Qualifications

• Bachelor's degree in computer science/Engineering, data science, or a related field. Master's degree preferred
• At least five plus years' experience as a machine learning engineer, deploying models in production
• Strong proficiency in Python and software engineering principles
• Solid understanding of machine learning fundamentals and model lifecycle management
• Experience with cloud platforms, containerization, and infrastructure management
• Familiarity with DevOps practices and automation tools
• Expertise in GenAI frameworks, prompt engineering, and model serving
• Ability to manage GPU/TPU resources and optimize model serving frameworks
• Experience in developing agentic systems and multi-agent architectures
• Proven track record in cost optimization in AI deployments
• Experience working in fast paced environment and independent worker

Pay

Payrate 75 - 90 per hour depending on experience.