Machine Learning Engineer

Job Description

Job Description

Machine Learning Engineer

$150k - $220k

Who We Are.

Wynd Labs is an early-stage startup that is on a mission to make public web data accessible for AI through contributions to Grass.

Grass is a network sharing application that allows users to share their unused bandwidth. Effectively, this is a residential proxy network that directly rewards individual residential IPs for the bandwidth they provide.

Grass will route traffic equitably among its network and meter the amount of data that each node provides to fairly distribute rewards.

In non-technical terms : Grass unlocks everyone's ability to earn rewards by simply sharing their unused internet bandwidth on personal devices (laptops, smartphones).

This project is for those who lead with initiative and seek to challenge themselves and thrive on curiosity.

We operate with a lean, highly motivated team who revel in the responsibility that comes with autonomy. We have a flat organizational structure, the people making decisions are also the ones implementing them.

We are driven by ambitious goals and a strong sense of urgency. Leadership is given to those who show initiative, consistently deliver excellence and bring the best out of those around them.

Join us if you want to set the tone for a fair and equitable internet.

The Role.

We are looking for a Machine Learning Engineer who is skilled and has significant experience in developing machine learning models.

You will join a small, innovative team and lead efforts to advance our capabilities, drive model development, and support our vision for a future where Grass is transformative in the evolution of the internet.

Who You Are.

• Bachelor's, Master's, or Doctoral degree in Data Science, Computer Science, Statistics, or a related field.
• A minimum of 3 years of work or research experience dealing with large datasets.
• Strong coding skills in Python or other object-oriented programming languages.
• Graduate-level knowledge of statistics, including but not limited to hypothesis testing, regression analysis, and probability.
• Excellent work ethic and the ability to thrive in a fast-paced startup environment.
• Strong problem-solving skills and attention to detail.
• Good communication skills, with the ability to articulate complex data concepts to non-technical stakeholders.
• Experience working in a high output team.

What You'll Be Doing.

• Developing, fine-tuning, and deploying LLMs for various NLP tasks such as text generation, summarization, translation, and sentiment analysis.
• Designing and implementing pipelines for processing and analyzing large text datasets.
• Analyzing and interpreting complex time series data to provide actionable insights and solutions.
• Designing, implementing, and maintaining data-driven models and algorithms.
• Collaborating with cross-functional teams to understand data needs and deliver timely solutions.
• Ensuring data quality and integrity throughout all processes.
• Utilizing Optical Character Recognition (OCR) technology to convert different types of documents into editable and searchable data.
• Continuously researching and implementing best practices in data science and machine learning.
• Contributing to the development and improvement of internal data processing tools and infrastructure.

Why Work With Us.

• Opportunity. We are at at the forefront of developing a web-scale crawler and knowledge graph that allows ordinary people to participate in the process, and share in the benefits of AI development.
• Culture. We're a lean team working together to achieve a very ambitious goal of improving access to public web data and distributing the value of AI to the people.

We prioritize low ego and high output.

• Compensation. You'll receive a competitive salary and equity package.
• Resources and growth. We're well-capitalized, with backing from leading venture funds like Polychain, Tribe, NLH, Hack, BH Digital, and more.

We keep a lean team, and this is a rare opportunity to join. You'll learn a lot and grow as our company scales