Machine Learning Engineer, Early Stage Project

Key Skills

Aartificial intelligence, Apache Beam, Apache Flink, Apache Hadoop, Effective communication skills, GoLang, JAX framework, Large Language Models - LLMs, Machine learning techniques, MLOps tools, Python Programming, PyTorch, SPARK Programming, TensorFlow, Writing

Job Description

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.

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.

At X, we don't just accept difference - we celebrate it, we support it, and we thrive on it for the benefit of our employees, our products and our community. We are proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to 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.

If you have a disability or special need that requires accommodation, please contact us at: x-accommodation-request@x.team.