ML Engineer I

We are seeking an experienced **AI Developer + Testing Specialist** with 6+ years of hands-on experience in AI/ML development, testing, and implementation across multiple AI platforms including Copilot, Claude, and other major AI tools. This role requires expertise in developing robust AI applications, comprehensive testing methodologies, quality assurance, and integration with enterprise systems. ## Key Responsibilities ### Development & Implementation - Design, develop, and deploy AI-powered applications and solutions using Copilot, Claude, and other major AI platforms - Create custom AI workflows, prompts, and integrations tailored to business requirements - Develop RAG (Retrieval Augmented Generation) systems, chatbots, and conversational AI applications - Implement API integrations with various AI models and services - Write clean, maintainable, and well-documented code following best practices and coding standards - Collaborate with product teams to understand requirements and translate them into technical specifications ### Testing & Quality Assurance - Develop comprehensive test strategies and test plans for AI applications - Perform functional, integration, performance, and security testing of AI-powered solutions - Conduct prompt engineering validation and optimization testing - Create and maintain automated test suites for AI/ML pipelines - Perform edge case and adversarial testing to identify model limitations and vulnerabilities - Validate output quality, accuracy, latency, and consistency across different AI models - Document test results, defects, and recommendations with detailed analysis ### AI Model Evaluation & Optimization - Evaluate and compare different AI models (GPT-4, Claude, Copilot, LLaMA, etc.) for specific use cases - Assess model performance, accuracy, cost-effectiveness, and suitability - Fine-tune prompts and configurations for optimal performance - Monitor model performance in production and recommend improvements - Conduct A/B testing and performance benchmarking ### Documentation & Knowledge Management - Create technical documentation for AI implementations and testing procedures - Develop training materials and best practice guides for AI tool usage - Maintain comprehensive records of testing methodologies and results - Document lessons learned and recommendations for future projects ### Collaboration & Communication - Work cross-functionally with data scientists, engineers, product managers, and stakeholders - Present findings, recommendations, and test results to technical and non-technical audiences - Participate in code reviews and peer testing sessions - Contribute to team knowledge sharing and continuous improvement initiatives --- ## Required Qualifications ### Experience - **6+ years** of professional experience in AI/ML development or testing - **3+ years** of hands-on experience with Copilot, Claude, or similar LLM-based platforms - **2+ years** of dedicated testing and QA experience with AI/ML systems - Proven experience developing production-grade AI applications - Experience with multiple AI platforms and models (OpenAI, Anthropic, Microsoft, Google, Meta, etc.) ### Technical Skills - **Programming Languages:** Python, JavaScript/TypeScript, Java, or similar (Python preferred) - **AI/ML Frameworks:** LangChain, LlamaIndex, OpenAI API, Anthropic API, Azure OpenAI, Copilot - **Testing Frameworks:** pytest, Selenium, Jest, or similar automated testing tools - **API Development & Integration:** RESTful APIs, webhooks, real-time integrations - **Version Control:** Git, GitHub, GitLab - **Cloud Platforms:** Azure, AWS, Google Cloud (at least one) - **Prompt Engineering:** Advanced knowledge of prompt design, optimization, and validation ### Domain Knowledge - Deep understanding of Large Language Models (LLMs) and their capabilities/limitations - Knowledge of RAG (Retrieval Augmented Generation) systems and vector databases - Understanding of AI ethics, bias detection, and responsible AI practices - Familiarity with AI security, data privacy, and compliance requirements - Knowledge of NLP/NLU concepts and applications ### Education & Certifications - Bachelor's degree in Computer Science, Software Engineering, Computer Engineering, or related field - OR equivalent professional experience (6+ years) in place of formal education - Relevant certifications (AI/ML, Cloud, QA) are a plus --- ## Preferred Qualifications - **Advanced Certifications:** AWS Certified Machine Learning, Microsoft Azure AI Engineer, Google Cloud AI Engineer - **Master's degree** in Computer Science, Artificial Intelligence, or related field - Experience with advanced testing methodologies (chaos engineering, security testing, load testing) - Hands-on experience with enterprise AI platforms and tools - Experience with Agile/DevOps methodologies and CI/CD pipelines - Published work, patents, or contributions to open-source AI projects - Experience with vector