Staff ML Engineer — Hybrid Role with AI Model Optimization

Bot Jobs; Camden (TN); Hybrid; USD 150,000 - 230,000; Full time

Benefits offered by this job

Hybrid work model

Global company opportunities

Job summary

NiCE is seeking a Staff Machine Learning Engineer to join NiCE Labs Research to advance model architecture and evaluation for Cognigy’s platform. You will optimize AI models, evaluate them with human and automated metrics, and work across teams to drive improvements in quality and cost.

We value collaboration, strong Python and ML framework skills, and experience with cloud ML infra. The role includes NiCE-FLEX hybrid work options and opportunities to influence cutting-edge AI systems.

Qualifications

• MS in computer science, machine learning, data science, or related field.
• 3+ years of post-graduate, hands-on experience with ML models, including training, fine-tuning, and evaluation.
• Experience with model optimization techniques such as quantization, distillation, or efficient inference.
• Experience designing evaluations or benchmarks for AI systems, including subjective or human-rated measures.
• Proficiency in Python and PyTorch or TensorFlow.
• Experience with cloud ML infrastructure (AWS, Azure, or GCP) for model testing and deployment.
• Ability to build working relationships with cross-functional teams, keep pace with a fast-changing field and shifting priorities, and present clearly to internal and external stakeholders.

Responsibilities

• Monitor the field for new state-of-the-art models and assess their relevance to Cognigy use cases.
• Design and run model evaluations, including human-judged protocols for generated output and validation of automated metrics against human ratings.
• Design and execute optimization strategies (fine-tuning, quantization, distillation, efficient inference) to improve quality, reduce latency, and lower cost.
• Deploy and benchmark open-weight models on cloud platforms and compare platforms for hosting.
• Provide technical review and guidance on teammates' model optimization work.
• Communicate results and recommendations to technical and non-technical stakeholders.

Skills

Python

PyTorch

Cloud ML

Model evaluation

ML optimization

Education

MS in CS/Data Science

Tools

Docker

Kubernetes

GPU inference

Job description

NiCE is seeking a Staff Machine Learning Engineer to join NiCE Labs Research to advance model architecture and evaluation for Cognigy’s platform. You will optimize AI models, evaluate them with human and automated metrics, and work across teams to drive improvements in quality and cost.

We value collaboration, strong Python and ML framework skills, and experience with cloud ML infra. The role includes NiCE-FLEX hybrid work options and opportunities to influence cutting-edge AI systems.