Senior Applied ML Research Engineer, Early Stage Project

About X:

X is Alphabet’s moonshot factory with a mission of inventing and launching “moonshot” technologies that could someday make the world a radically better place. We are a diverse group of inventors and entrepreneurs who build and launch technologies that aim to improve the lives of millions, even billions, of people. Our goal: 10x impact on the world’s most intractable problems, not just 10% improvement. We approach projects that have the aspiration and riskiness of research with the speed and ambition of a startup. As an innovation engine, X focuses on repeatedly turning breakthrough-technology ideas into the foundations for large, sustainable businesses.

About the team:

We're a small, passionate and driven team of experienced ML researchers, software engineers and product managers on a mission to make the practice of law radically more efficient and accurate. Our legal moonshot is focusing on de-risking our technology quickly, refining our tech prototypes, running experiments with partners and developing a valuable product for our users.  Our culture is one of mutual care & respect, individual competence and most important of all, fun!

About the role:

As a Senior Applied Research Engineer, you will be responsible for building AI systems that can perform previously impossible tasks or achieve unprecedented levels of performance. We're looking for people with solid engineering skills (e.g. designing, implementing, and improving models achieving specific tasks), writing bug-free machine learning code, and building the science behind the algorithms employed.

How you will make 10X Impact:

• Act like an owner; be fearless in diving deep, asking questions, proposing solutions, establishing consensus and then making things happen.
• Work effectively with cross-functional teams of engineers, product managers, and domain experts
• Provide direction and focus in areas of high ambiguity 
• Enjoy mentoring others and helping the team grow
• Develop deep expertise with the team’s technical stack,  make targeted contributions and move fast in the work of experimentation

What you should have:

• MSc or PhD degree in computer science, mathematics, applied stats, machine learning
• 6+ years experience in NLP applied research and high-performance implementations of machine learning algorithms and productionization
• Track record of delivering on larger, multi-quarter projects, including directing the work of junior team members.
• Experience translating research concepts or novel techniques into robust, production-ready systems
• Proficiency in MLOps, including model deployment, versioning and performance monitoring in production environments
• Excel at building strong relationships with stakeholders at all levels
• Strong proficiency in Python and software engineering best practices (testing, designing architectures, version control, etc)  
• Achieved strong results with sophisticated model prompting, and with (at least one of) fine-tuning or applying RL to large language models
• Excellent written and verbal communication skills, e.g. design docs, PR descriptions
• Ability to work in the Mountain View office at least 3 days per week to interface with researchers and engineering

It’d be great if you had these:

• Deep interest in the potential transformative effects of advanced AI systems and commitment to ensuring their safe development
• Startup experience iterating fast and explore multiple strategies to optimize performance
• Passion for delighting users, but also extracting energy from both good and difficult feedback
• Significant success with building AI software and systems for specific industries, either as research publications at top PL or ML venues, or as open source artifact(s)
• Consistent track record of delivering high quality solutions to large, complex software problems

The US base salary range for this full-time position is $165,000 - $238,000 + bonus + equity + benefits. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your location during the hiring process. 
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits.