À propos
Machine Learning Lead
to drive the development of advanced ML models that support real-world, high-impact applications. This role will focus on building production-grade machine learning systems, collaborating closely with engineering and product teams, and ensuring models are reliable, scalable, and aligned with real operational requirements.
The ideal candidate has strong hands-on ML experience, is comfortable owning projects end-to-end, and thrives at the intersection of research, software engineering, and applied problem-solving.
Key Responsibilities
Lead the design, development, and deployment of machine learning models for complex, real-world datasets
Translate ambiguous problem statements into well-defined ML solutions and evaluation strategies
Build and maintain ML pipelines, including data preprocessing, training, validation, and monitoring
Collaborate cross-functionally with software engineers, product, and domain experts to integrate models into production systems
Evaluate model performance, robustness, and generalization using appropriate metrics and validation frameworks
Contribute to technical architecture decisions and establish ML best practices across the team
Mentor junior team members and provide technical guidance on modeling and implementation approaches
Stay current on advances in machine learning and assess applicability to internal use cases
Required Qualifications
Advanced degree (MS or PhD preferred) in Machine Learning, Computer Science, Engineering, or a related quantitative field
5+ years of applied machine learning experience, including deploying models into production
Strong proficiency in Python and common ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn)
Experience working with structured and/or high-dimensional data
Solid understanding of model evaluation, data leakage prevention, and performance tradeoffs
Experience collaborating with software engineering teams on production systems
Ability to communicate technical concepts clearly to both technical and non-technical stakeholders
Preferred Qualifications
Experience leading or owning ML projects from concept through deployment
Familiarity with MLOps tools and workflows (model versioning, monitoring, CI/CD for ML)
Background in regulated, safety-critical, or high-reliability environments
Exposure to cloud-based ML infrastructure and scalable data pipelines
What Success Looks Like
ML models are reliable, well-validated, and effectively integrated into production systems
Clear ownership and accountability for ML outcomes and performance
Strong collaboration across teams with minimal friction between research and engineering
Scalable, maintainable ML infrastructure that supports future growth
Why Join
High ownership and impact on core technology
Opportunity to shape ML strategy and technical direction
Collaborative, engineering-driven culture focused on quality and real-world outcomes
Seniority level Mid-Senior level
Employment type Full-time
Job function Medical Equipment Manufacturing
Benefits
Medical insurance
Vision insurance
401(k)
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Compétences linguistiques
- English
Avis aux utilisateurs
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