Machine Learning Engineer

About This Role

As a Machine Learning Engineer, you will own the end-to-end ML lifecycle, building and deploying production machine learning systems, including sophisticated content recommendation models and member-specific predictions to personalize the Bold experience and drive measurable health outcomes.

Responsibilities

• Develop and deploy production ML models that power content recommendation systems, member-specific predictions, and personalized experiences across the Bold platform
• Collaborate cross-functionally with data scientists, software engineers, and product managers to integrate ML capabilities into products and applications
• Build and optimize recommendation systems using supervised and unsupervised learning methods, Transformers, and state-of-the-art ML techniques
• Own the full ML lifecycle from experimentation and testing to deployment, monitoring, and iteration
• Establish best practices for model performance tracking, versioning, and continuous improvement
• Enable internal and external data products by creating robust ML pipelines and APIs that make predictions accessible to stakeholders

Requirements

• 3-5+ years developing and deploying machine learning models in production environments
• Proven track record building recommendation systems, predictive models, or ML-powered features
• Strong software engineering background with experience shipping production code
• Expert-level proficiency in Python, PyTorch, and Scikit-learn
• Deep understanding of content recommendation algorithms, collaborative filtering, embeddings, and Transformer architectures
• Strong foundation in software development principles, version control (Git), CI/CD practices
• Ability to translate complex technical concepts for non-technical stakeholders

Qualifications

• Bachelor's degree in Computer Science, Machine Learning, Data Science, Statistics, or related technical field
• 3-5+ years developing and deploying machine learning models in production environments

Nice to Have

• Master's or PhD in Computer Science, Machine Learning, Data Science, Statistics, or related technical field
• Experience with Generative AI models, building agentic workflows, MLOps tools and practices
• Experience with cloud platforms (AWS/GCP/Azure)
• Startup or high-growth environment experience
• Health, wellness, or healthcare industry experience

Skills

* Required skills

Benefits