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 and data pipelines 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.

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How you will make 10X Impact:

Explore, apply, and innovate state-of-the-art LLM & machine learning techniques to solve real-world problems
Lead the design and implementation of ML data platforms and service frameworks, including labeling workflows and sampling strategies
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
7+ years of on-the-job experience developing and training ML models for product use-cases
Proficiency in MLOps tasks such as deploying and versioning ML models in production environments and monitoring their performance

Experience doing win/loss analysis on model results and systematically finding efficient ways to boost wins and reduce losses
Experience with building data pipelines (e.g. Beam, Dataflow, Flume, Flink, Hadoop, Spark)
Experience testing, maintaining or launching software products, including experience with software design and architecture
Strong proficiency in coding with Python, Golang, or other equivalent languages.
Excellent written and verbal communication skills

It’d be great if you had these:

Experience applying LLMs for large scale document processing, including tasks such as annotation, entity extraction, etc.
Experience in ML modeling using TensorFlow, Pytorch or Jax/Flax
Experience in Google Cloud Platform and its Vertex AI solution and capabilities.
Consistent track record of delivering high quality solutions to large, complex software problems
Prior experience with setting the technical direction for small groups of engineers
Experience working in start-up like environments

The US base salary range for this full-time position is $160,000 – $210,000 + bonuses + 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.

Part time job Machine Learning Engineer, Early Stage Project Job ID- 1482

Amazon
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