Machine Learning 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 project is focusing on de-risking our technology, refining our tech prototypes, running experiments with partners and developing a product prototype and business plans. Our culture is one of mutual care & respect, individual competence and most important of all, fun!

About The Role

As an applied ML software engineer, you will own end-to-end development of breakthrough technologies that rely heavily on large language models. You will work on prompt optimization and evaluation, pipeline implementation and scalability, and production monitoring and performance. You will have the opportunity to fine-tune SOTA models with domain-specific knowledge to improve reasoning performance. You will work closely with domain experts to refine and iterate on the technology, and we will rely on you to apply your knowledge and expertise to come up with and implement novel and impactful ideas.

How You Will Make 10X Impact

• Explore, apply, and innovate state-of-the-art LLM & machine learning techniques to solve real-world problems
• Design and implement ML workflows, such as batch inference, agentic processes, active learning, fine tuning and data labeling
• Design and implement robust, automated, production-level software using horizontally scalable components
• Work effectively with cross-functional teams of engineers, product managers, and domain experts
• Provide direction and focus in areas of high ambiguity
  
  

What You Should Have

• Bachelors/Masters in Computer Science, or equivalent practical experience
• Experience in NLP applied research
• Professional experience in developing and training ML models for product applications
• Proficiency in MLOps, including model deployment, versioning and performance monitoring in production environments
• Ability to innovate ways to improve model accuracy and quantify drift, overfitting and regression
• Experience building pipelines for data processing (e.g. Beam, Flume, Flink, KubeFlow, Spark)
• Experience optimizing system/model performance (e.g. speed, cost, throughput)
• Strong proficiency in Python and standard software engineering practices (testing, designing architectures, version control, etc)
• Excellent written and verbal communication skills
  
  

It’d Be Great If You Had These

• Experience applying LLMs for large scale document processing, including tasks like annotation, entity extraction, etc.
• Experience designing agentic workflows
• Experience with knowledge graphs or retrieval-augmented generation
• Experience in ML modeling using TensorFlow, Pytorch or Jax/Flax
• Experience in Google Cloud Platform and Vertex AI
• Consistent track record of delivering high quality solutions to large, complex software problems
• Experience working in start-up like environments
  
  

The US base salary range for this full-time position is $136,000 - $185,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. 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, or benefits.