Senior Machine Learning Engineer

Job Responsibilities

• Build and optimize agentic AI workflows that enable users to dynamically interact with and refine outputs from ML systems
• Research and implement advanced ML and NLP techniques, including transformer-based models, embeddings, and retrieval-augmented generation
• Develop evaluation frameworks to assess accuracy, robustness, and usability of ML/LLM models in production environments
• Design, train, and deploy machine learning models for tasks such as classification, entity identification, information extraction, retrieval, topic discovery, and structured insight generation
• Architect and optimize RAG pipelines for grounding LLMs with enterprise data to ensure accuracy and reliability
• Collaborate with engineers, UX designers, and product managers to integrate AI-driven capabilities into Cresta’s platform
• Optimize ML pipelines and data processing systems to operate efficiently at scale

Qualifications

• Master's or Ph.D. in Computer Science, Machine Learning, AI, or a related field
• 5+ years of hands-on experience building and deploying ML models in production
• Strong knowledge of ML frameworks and NLP libraries (e.g., PyTorch, TensorFlow, Hugging Face, spaCy, NLTK)
• Solid experience with modern ML techniques including transformer architectures, embeddings, retrieval systems, and large-scale model training
• Experience designing and deploying Retrieval-Augmented Generation pipelines for enterprise use cases
• Familiarity with evaluation and benchmarking frameworks for ML/LLM models
• Strong passion for AI-driven innovation, with a proven ability to deliver impactful, production-grade solutions

Why Join Us

Role Responsibilities

• Build and optimize agentic AI workflows that enable users to dynamically interact with and refine outputs from ML systems
• Research and implement advanced ML and NLP techniques, including transformer-based models, embeddings, and retrieval-augmented generation
• Develop evaluation frameworks to assess accuracy, robustness, and usability of ML/LLM models in production environments
• Design, train, and deploy machine learning models for tasks such as classification, entity identification, information extraction, retrieval, topic discovery, and structured insight generation
• Architect and optimize RAG pipelines for grounding LLMs with enterprise data to ensure accuracy and reliability
• Collaborate with engineers, UX designers, and product managers to integrate AI-driven capabilities into Cresta’s platform
• Optimize ML pipelines and data processing systems to operate efficiently at scale

How to Join Jobright TNT

If this is your first time applying to a Jobright TNT role, the process works as follows:

1. Apply to your first Jobright TNT role
2. We review your background to determine if you meet the TNT quality bar
3. If qualified, your application is directly recommended to the employer
4. Once accepted into TNT, you may be:
• Invited to apply for other exclusive TNT-only roles
• Invited to private, invite-only hiring events with top startups

You will be notified of your TNT selection result.

PS: All Jobright TNT roles are 100% real, directly hired by top AI startups we partner with, and come with priority review and higher response rates than the normal application queue.