Essential
Member of Technical Staff: Research Scientist, Post-Training
Essential, San Francisco, California, United States, 94199
About Us
Essential AI’s mission is to deepen the partnership between humans and computers, unlocking collaborative capabilities that far exceed what could be achieved today. We believe that building delightful end-user experiences requires innovating across the stack - from the UX all the way down to models that achieve the best user value per FLOP.We are building a world-class multi-disciplinary team who are excited to solve hard real-world AI problems.The Role
The Research Scientist, Post-Training will lead our post-training research efforts to improve the efficiency, performance and robustness of our models. You will work cross-functionally to develop novel techniques for fine-tuning, adapting, and updating models to drive business value for our customers and enhance our products.What you’ll be working on
You will lead or be a core contributor to our research bets that advance the real-world capabilities of our models.You will collaborate closely with our product teams to close the loop between research and product, identify capability gaps and evaluate progress.Lead research initiatives focused on post-training models for enterprises; Design and execute research experiments to enhance the post-training capabilities of our models.Develop new algorithms and methods for efficient and effective model fine-tuning and adaptation.Construct synthetic datasets and evaluations for enterprise use-cases.Analyze results and draw insights to guide future research projects.Stay abreast of the latest advancements in post-training techniques (RLHF, RLAIF, DPO etc.) incorporating relevant findings into research projects and product development efforts.What we are looking for
Research experience with a focus on post-training and optimizing large language models using frameworks such as Megatron, DeepSpeed, MaxText, etc.You have strong ML fundamentals and first principles thinking that guides your approach to research.You have experience of coming up with new methods or improving existing techniques in ML or related fields.Proficiency in programming languages commonly used in machine learning research such as Python.Strong problem solving, analytical, communication, and collaboration skills.You enjoy building things from the ground up in a fast-paced, collaborative environment.(Bonus) Previous experience of improving products and end user experience through machine learning models.We encourage you to apply for this position even if you don’t check all of the above requirements but want to spend time pushing on these techniques.We are based in-person in SF and work fully onsite 5 days a week. We offer relocation assistance to new employees.The base pay range target for the role seniority described in this job description is up to $225,000 in San Francisco, CA. Final offer amounts depend on various job-related factors, including where you place on our internal performance ladders, which is based on factors including past work experience, relevant education, and performance on our interviews and our benchmarks against market compensation data. In addition to cash pay, full-time regular positions are eligible for equity, 401(k), health benefits, and other benefits like daily onsite lunches and snacks; some of these benefits may be available for part-time or temporary positions.Essential AI commits to providing a work environment free of discrimination and harassment, as well as equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.
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Essential AI’s mission is to deepen the partnership between humans and computers, unlocking collaborative capabilities that far exceed what could be achieved today. We believe that building delightful end-user experiences requires innovating across the stack - from the UX all the way down to models that achieve the best user value per FLOP.We are building a world-class multi-disciplinary team who are excited to solve hard real-world AI problems.The Role
The Research Scientist, Post-Training will lead our post-training research efforts to improve the efficiency, performance and robustness of our models. You will work cross-functionally to develop novel techniques for fine-tuning, adapting, and updating models to drive business value for our customers and enhance our products.What you’ll be working on
You will lead or be a core contributor to our research bets that advance the real-world capabilities of our models.You will collaborate closely with our product teams to close the loop between research and product, identify capability gaps and evaluate progress.Lead research initiatives focused on post-training models for enterprises; Design and execute research experiments to enhance the post-training capabilities of our models.Develop new algorithms and methods for efficient and effective model fine-tuning and adaptation.Construct synthetic datasets and evaluations for enterprise use-cases.Analyze results and draw insights to guide future research projects.Stay abreast of the latest advancements in post-training techniques (RLHF, RLAIF, DPO etc.) incorporating relevant findings into research projects and product development efforts.What we are looking for
Research experience with a focus on post-training and optimizing large language models using frameworks such as Megatron, DeepSpeed, MaxText, etc.You have strong ML fundamentals and first principles thinking that guides your approach to research.You have experience of coming up with new methods or improving existing techniques in ML or related fields.Proficiency in programming languages commonly used in machine learning research such as Python.Strong problem solving, analytical, communication, and collaboration skills.You enjoy building things from the ground up in a fast-paced, collaborative environment.(Bonus) Previous experience of improving products and end user experience through machine learning models.We encourage you to apply for this position even if you don’t check all of the above requirements but want to spend time pushing on these techniques.We are based in-person in SF and work fully onsite 5 days a week. We offer relocation assistance to new employees.The base pay range target for the role seniority described in this job description is up to $225,000 in San Francisco, CA. Final offer amounts depend on various job-related factors, including where you place on our internal performance ladders, which is based on factors including past work experience, relevant education, and performance on our interviews and our benchmarks against market compensation data. In addition to cash pay, full-time regular positions are eligible for equity, 401(k), health benefits, and other benefits like daily onsite lunches and snacks; some of these benefits may be available for part-time or temporary positions.Essential AI commits to providing a work environment free of discrimination and harassment, as well as equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.
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