Turing is seeking a hands-on Machine Learning Senior Staff Engineer to lead cross-functional teams building and deploying cutting-edge LLM and ML systems to drive reliable, high-performance systems that translate research breakthroughs into measurable business impact.
Requirements
- Strong background in Machine Learning, NLP, and modern deep learning architectures (Transformers, LLMs).
- Hands-on experience with frameworks such as PyTorch, TensorFlow, Hugging Face, or DeepSpeed
- Hands-on experience in Docker for Production deployment.
- Proven experience managing teams delivering ML/LLM models in production environments.
- Knowledge of distributed training, GPU/TPU optimization, and cloud platforms (AWS, GCP, Azure).
- Familiarity with MLOps tools like MLflow, Kubeflow, or Vertex AI for scalable ML pipelines.
- Experience building Agentic applications
Responsibilities
- Lead and mentor a cross-functional team of ML engineers, data scientists, and MLOps professionals.
- Oversee the full lifecycle of LLM and ML projects — from data collection to training, evaluation, and deployment.
- Collaborate with Research, Product, and Infrastructure teams to define goals, milestones, and success metrics.
- Provide technical direction on large-scale model training, fine-tuning, and distributed systems design.
- Implement best practices in MLOps, model governance, experiment tracking, and CI/CD for ML.
- Manage compute resources, budgets, and ensure compliance with data security and responsible AI standards.
- Communicate progress, risks, and results to stakeholders and executives effectively.
Other
- Bachelor’s or Master’s in Computer Science, Engineering, or related field (PhD preferred).
- Excellent leadership, communication, and cross-functional collaboration skills.
- Overlap of 6 hours with PST time zone is mandatory.
- Work in a fully remote environment
- 5 days a week
