REF: 10771

Machine Learning Engineer (GenAILLM) | Fully Remote | Permanent
Location: United States (Remote Only)
Contract Type: Permanent
Salary: $160,000 – $220,000 + Equity
About the Company
Join a cutting-edge AI startup that has recently achieved Unicorn status and is preparing for Series B funding. With a team of around 100 people, they are rapidly expanding and looking for top-tier talent to drive their GenAI and LLM initiatives.

Key Responsibilities

• Develop, deploy, and manage the full lifecycle of ML models for large-scale applications
• Work on natural language understanding (NLU), web search & ranking, recommendations, personalization, and conversational AI
• Optimize and fine-tune LLMs and GenAI models for production use
• Collaborate with data scientists, engineers, and product teams to integrate ML models into real-world applications
• Ensure models are scalable, efficient, and continuously improving

Key Requirements

• Strong background in Machine Learning (ML), Deep Learning (DL), and Large Language Models (LLMs)
• Hands-on experience with ML frameworks (TensorFlow, PyTorch, Hugging Face, etc.)
• Proficiency in Python and ML libraries (NumPy, Pandas, Scikit-Learn)
• Experience with cloud-based ML deployment (AWS, GCP, Azure)
• Prior experience in AI-driven applications like search, recommendation systems, or conversational AI
• A passion for cutting-edge AI research and real-world applications

Why Join?

• Be part of a fast-growing company
• Work on state-of-the-art GenAI and LLM projects
• Fully remote role with competitive salary + equity
• Opportunity to shape the future of AI-driven applications

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- Consultant: Dylan Martin
At Orbis Group, we are committed to creating an inclusive and diverse workplace. Research indicates that candidates, especially from underrepresented backgrounds, often hesitate to apply for jobs if they don’t meet every qualification.
If you’re excited about a role but don’t perfectly align with every requirement, we encourage you to apply. Your unique skills and experiences may be the perfect fit for the job or other opportunities that arise

• Develop, deploy, and manage the full lifecycle of ML models for large-scale applications
• Work on natural language understanding (NLU), web search & ranking, recommendations, personalization, and conversational AI
• Optimize and fine-tune LLMs and GenAI models for production use
• Collaborate with data scientists, engineers, and product teams to integrate ML models into real-world applications
• Ensure models are scalable, efficient, and continuously improvin