AI/ML Engineer
Description For AI/ML Engineer
MLabs is seeking an AI/ML Engineer to develop responsible, explainable, and neuroinclusive AI models for workplace analytics. The role focuses on designing and deploying machine learning models that analyze team dynamics and provide actionable insights while maintaining ethical AI standards and GDPR compliance. The position offers a unique opportunity to work with cutting-edge AI technologies including NLP, deep learning, and MLOps in a remote-first environment. The ideal candidate will have strong experience in machine learning deployment, cloud technologies, and a commitment to ethical AI development. This role combines technical expertise with a focus on creating inclusive workplace solutions, offering equity options and the chance to shape the product from its early stages.
Responsibilities For AI/ML Engineer
- 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 decision making
- Optimize models for efficiency, performance, and fairness, reducing algorithmic bias
- Deploy AI models to production-ready cloud environments
- Collaborate with product and UX teams to ensure AI insights are interpretable
- 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
Requirements For AI/ML Engineer
- 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
- 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 with containerization
- Understanding of privacy-first AI, differential privacy, and federated learning is a bonus
- Passion for neuroinclusive and ethical AI development
Benefits For AI/ML Engineer
- 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
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