Note: The job is a remote job and is open to candidates in USA. The Cypress Group is hiring a Staff Machine Learning Engineer for a growing digital services company developing AI-powered product capabilities involving sensitive consumer information. The role will take machine learning projects from exploration through production, build language-model and data systems, establish evaluation and safety practices, and guide architecture while mentoring engineers.

Responsibilities

• Design, build, deploy, and maintain machine learning features used in customer-facing products
• Develop applications that use language models, information retrieval, classification, ranking, and structured data extraction
• Turn unstructured content and user activity into useful signals for search, recommendations, personalization, and content organization
• Build dependable data and model pipelines for development, testing, production inference, and performance analysis
• Establish practical methods for evaluating accuracy, usefulness, safety, and business impact
• Create safeguards for sensitive use cases, including automated checks, human review, testing for misuse, and clear escalation procedures
• Monitor production systems for changes in quality, reliability, speed, and operating cost
• Work with product managers, software engineers, data specialists, and domain experts to translate business needs into measurable technical outcomes
• Guide technical architecture, develop shared engineering practices, and mentor other engineers

Skills

• - Substantial experience delivering machine learning systems in production
• - Advanced programming skills in Python or a comparable language
• - Hands-on experience with modern natural language processing and generative AI techniques
• - Strong understanding of machine learning, statistical analysis, experimentation, and model evaluation
• - Experience building reliable data, training, inference, and evaluation workflows
• - Familiarity with production practices such as automated testing, version control, repeatable deployments, observability, and incident response
• - Experience processing large datasets using cloud-based or distributed systems
• - Ability to turn loosely defined product questions into clear technical plans and success measures
• - Strong written and verbal communication across technical and nontechnical teams
• - Search, retrieval-augmented generation, recommendation systems, or ranking models
• - Products that handle sensitive information or operate in a regulated setting
• - Privacy, security, auditability, or responsible-AI reviews
• - Real-time data, product analytics, or controlled experiments
• - Rapid development of simple prototypes for user testing
• - Adversarial testing and defenses for language-model applications
• - Human-in-the-loop review systems

Company Overview