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Senior Machine Learning Engineer

Remote · Switzerland Full-time

A leading technology company specializing in content safety solutions is seeking a Senior Machine Learning Engineer to support their remote team. This position offers a dynamic environment focused on developing scalable ML systems that ensure safe and appropriate content across diverse formats. Join our client's innovative team to tackle impactful AI challenges. This is a hybrid role in NYC. There is no application deadline for this role. *Senior Machine Learning Engineer Responsibilities:* * Design, implement, and enhance ML systems to detect harmful, sensitive, or policy-relevant content across various modalities.

  • Manage the entire lifecycle of model development, including data collection, experimentation, evaluation, deployment, and ongoing monitoring.
  • Develop multimodal detection techniques utilizing vision, text, audio, and large language models where applicable.
  • Create evaluation frameworks with datasets, labeling strategies, and performance monitoring to ensure model reliability.
  • Collaborate with cross-disciplinary teams to translate safety requirements into technical solutions and drive experimentation for model improvement.

*Senior Machine Learning Engineer Qualifications:* * Minimum of 5-6 years of experience building, deploying, and maintaining ML systems in production.

  • Proficiency with modern ML frameworks such as PyTorch and experience with vision, text, audio, or multimodal models.
  • Deep understanding of ML evaluation processes, including dataset design, threshold calibration, and trade-offs between precision and recall.
  • Ability to develop ML solutions that optimize quality, reliability, latency, scalability, and user impact.
  • Strong commitment to responsible ML practices, including bias mitigation, edge case handling, and assessment of model failure modes.

*Perks and Benefits:* * Medical, Dental, and Vision Insurance.

  • Life Insurance.
  • 401(k) Program.
  • Commuter Benefit.
  • eLearning and Ongoing Training.
  • Education Reimbursement.

Eligibility requires working over 30 hours per week on an assignment lasting at least 10 weeks. If you meet the qualifications and are excited about this opportunity, apply today! Our team will connect with you to discuss next steps, support you through the interview process, and advocate for your success.

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