Join Essential AI as a Research Engineer, Post-Training!

At Essential AI, we are on a fascinating mission to enhance the synergy between humans and computers, vastly expanding collaborative possibilities beyond current limitations. Our goal is clear: to create exceptional user experiences by spearheading innovation from the user interface to the most efficient computational models. Supported by leading investors like March Capital, Thrive Capital, AMD, Franklin Venture Partners, Google, KB Investment, and NVIDIA, we're fostering a compact, dynamic team poised to achieve groundbreaking advances in the AI domain.

About the Role: Research Engineer, Post-Training

As a key member of our technical staff, your primary responsibility will be to develop and implement strategies for optimizing and refining AI models post initial training. This includes enhancing model performance, robustness, and efficiency. Collaboration across teams will be essential to pinpoint opportunities for post-training improvements and to evaluate the impacts on model functionality.

Key Responsibilities

• Lead and significantly contribute to research initiatives that enhance real-world applications of our AI models.
• Work closely with product teams to bridge research and product development, identifying gaps and assessing improvements.
• Develop innovative post-training techniques to advance machine learning model optimization.
• Conduct benchmarking and assessments of various post-training strategies across multiple datasets and model architectures.
• Analyze outcomes to uncover insights into model behaviors and identify enhancement opportunities.
• Implement models and algorithms for post-training phases, optimizing for performance and scalability in production settings.
• Engage with research scientists and engineers to discover further areas for post-training enhancements.

What We're Looking For

• Proven research experience focused on post-training and optimization of large language models, with proficiency in frameworks like Megatron, DeepSpeed, MaxText, etc.
• Solid foundation in machine learning principles guiding innovative research approaches.
• Background in devising or enhancing methods within ML or related fields.
• Experience with data engineering tasks such as optimizing data pipelines, feature engineering, and model assessment.
• Strong programming skills in Python, C++, or Java, and familiarity with ML deployment and orchestration.
• Excellent problem-solving, analytical, and communication abilities, capable of handling complex data analyses and deriving practical insights.
• A passion for building innovative solutions in a collaborative, fast-paced environment.

Located in San Francisco, Essential AI values in-person collaboration and supports relocation for qualified candidates.

Apply Today!

If you are eager to push boundaries in machine learning techniques and enjoy a challenge, apply to become a vital part of Essential AI. Even if you don't meet every criterion, we encourage you to take a leap and submit your application—your unique experience might be exactly what we need!

Essential AI is excited to see how you can contribute to our mission of making AI more effective and accessible. Join us in shaping the future of human-computer collaboration!