AI/ML Engineer

Summary

Join our team as an AI/ML Engineer to design, develop, and deploy responsible and explainable AI models for workplace analytics. You will work with structured and unstructured data, implementing explainable AI techniques and ensuring fairness and compliance with ethical AI standards and GDPR. Responsibilities include model optimization, deployment to cloud environments, collaboration with product and UX teams, and ensuring data privacy and security. You will need experience in machine learning, deep learning, or NLP, proficiency in Python and relevant libraries, and knowledge of MLOps best practices. The role offers a fully remote, flexible working culture, equity options, and the opportunity to shape the product and tech stack.

Requirements

• Experience in machine learning, deep learning, or NLP, with real-world model deployment experience
• Proficiency in Python, TensorFlow/PyTorch, and Scikit-learn
• Experience working with vector databases, embeddings, and LLMs (e.g., OpenAI, Hugging Face, RAG)
• Knowledge of MLOps best practices, including CI/CD for ML, monitoring, and versioning
• Strong understanding of AI fairness, bias mitigation, and explainability techniques
• Experience deploying models in cloud environments (AWS/GCP/Azure) with containerization (Docker, Kubernetes)

Responsibilities

• Design, train, and deploy AI/ML models for team analytics, psychometric analysis, and predictive insights
• Work with structured and unstructured data, ensuring quality, consistency, and compliance
• Implement explainable AI (XAI) techniques to ensure transparency in decisionmaking
• Optimize models for ehiciency, performance, and fairness, reducing algorithmic bias
• Deploy AI models to production-ready cloud environments (AWS/GCP/Azure, Kubernetes, Docker)
• Collaborate with product and UX teams to ensure AI insights are interpretable and useful for users
• Ensure data privacy, security, and compliance (GDPR, ISO 27001, AI Act)
• Research and integrate state-of-the-art NLP, computer vision, and deep learning models as needed

Preferred Qualifications

• Understanding of privacy-first AI, diherential privacy, and federated learning is a bonus
• Passion for neuroinclusive and ethical AI development

Benefits

• Work on a meaningful product that makes workplaces more inclusive
• Fully remote, flexible working culture
• Opportunity to shape the product and tech stack from an early stage
• Equity options in a growing company