Staff Machine Learning Engineer

webAI is the first end-to-end private AI platform. Enterprises and Governments use webAI to bring AI to their data, powering specialized intelligence trained on their own knowledge and compounding in value with every use. We are seeking an experienced Staff Machine Learning Engineer with a strong background in Large Language Models (LLMs) and/or Mixture of Experts (MoEs). The ideal candidate will have a proven track record of developing and deploying advanced AI models. You will lead core product initiatives across on-device inference optimization, quantization, RAG, agentic framework and/or tool calling.

Responsibilities

Lead core product initiatives across on-device inference optimization, quantization, RAG, agentic framework and/or tool calling; Be responsible for end-to-end delivery working cross functionally with other engineering functions and lead the sub-team; Lead the development and optimization of Large Language Models and Mixture of Experts models; Collaborate with cross-functional teams to integrate ML models into our platform; Conduct cutting-edge research in machine learning, with a focus on improving the performance and efficiency of LLMs; Stay abreast of the latest advancements in AI and ML, and apply this knowledge to improve our models and methodologies; Mentor junior engineers and contribute to the team’s knowledge sharing and best practices

Requirements

Advanced degree (Ph.D. preferred) in Computer Science, or a related field; Proven track record of building and innovations through publications or industry experience; Minimum of 6 years of experience in machine learning, with specific expertise in Large Language Models and Mixture of Experts; Strong programming skills in Python and machine learning frameworks like TensorFlow and/or PyTorch; Demonstrated ability to lead complex projects and work collaboratively in a team environment; Excellent problem-solving skills and a passion for innovation

Nice to have

Experience with cloud computing services (AWS, Azure, GCP); Knowledge of Big Data technologies (Hadoop, Spark); Familiarity with containerization and orchestration technologies (Docker, Kubernetes); Publications or presentations in recognized Machine Learning journals or conferences

Benefits

Competitive salary; Comprehensive health, dental, and vision benefits package; 401(k) match; Equity options; $200/month Health & Wellness stipend; Continuing Education support; $500/year Function Health subscription; Free parking for in-office employees; Flexible Time Off (FTO); Parental leave for eligible employees; Supplemental life insurance