Senior Machine Learning Specialist

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You will be responsible for developing and implementing machine learning solutions that power our AI-native platform. This role requires expertise in custom model development, transformer architectures, and production deployment of ML systems.

Responsibilities

  • Design and develop custom machine learning models for specific business use cases.
  • Implement and optimize transformer architectures for natural language processing tasks.
  • Develop and maintain ML pipelines for data preprocessing, model training, and inference.
  • Work with large language models and implement fine-tuning strategies.
  • Implement retrieval-augmented generation (RAG) systems and optimize their performance.
  • Collaborate with engineering teams to deploy ML models in production environments.
  • Monitor and maintain model performance in production, implementing retraining strategies as needed.
  • Conduct research on emerging ML techniques and evaluate their applicability to our platform.
  • Mentor junior ML engineers and contribute to best practices within the team.

Required Skills and Qualifications

  • Master's degree or PhD in Computer Science, Machine Learning, or a related field, or equivalent practical experience.
  • 5+ years of experience in machine learning development and deployment.
  • Strong programming skills in Python and experience with ML frameworks (PyTorch, TensorFlow, or similar).
  • Deep understanding of transformer architectures and their applications in NLP.
  • Experience with large language models and fine-tuning techniques.
  • Proficiency in implementing and optimizing RAG systems.
  • Experience with ML model deployment and production monitoring.
  • Strong understanding of data preprocessing, feature engineering, and model evaluation techniques.
  • Experience with cloud platforms and ML infrastructure (AWS SageMaker, Google Vertex AI, or similar).
  • Excellent problem-solving skills and attention to detail.
  • Strong communication and interpersonal skills.

Preferred Qualifications

  • Experience with MLOps and ML pipeline orchestration tools.
  • Knowledge of distributed training and model optimization techniques.
  • Experience with vector databases and similarity search algorithms.
  • Familiarity with reinforcement learning and multi-agent systems.