Applied Machine Learning Research Scientist

Applied Machine Learning Research Scientist

Coactive AI

• USD 190K-250K
• Full time
• San Francisco, California, United States
• Hybrid

Coactive makes it easy to search, filter, and analyze visual content. Increasingly image and video data captures the content we watch, the products we buy, and the work we do, and already represents 80% of internet traffic. But rather than being an asset, visual content is often a tax or even a liability because it is so hard to work with and understand.

Coactive solves this by bringing structure to unstructured visual data. Rather than spending months (or years) building complex infrastructure, data teams can unlock the value of their visual data in minutes to power use cases such as content understanding and moderation, search, and analytics. Coactive was founded by experts who shaped the fields of high-performance deep learning and data-centric AI.

We have the scars from building and working with the first generation of modern machine learning systems at Google, Meta, Pinterest, eBay, Lyft, and other leading organizations. Through our decades of experience, we have developed a playbook to democratize the toughest parts of machine learning systems; no PhD required. This is an exceptional opportunity to work with one of Forbes' top 50 AI companies, backed by key investors such as Andreesen Horowitz and Bessemer Ventures.

This position is truly a chance to be part of a category-defining team that is attracting top-tier talent interested in pushing the boundaries of what's possible in AI. We’re seeking an Applied Machine Learning Research Scientist to collaborate closely with our top-tier machine learning and data systems experts, driving innovation and creating the foundation for groundbreaking machine learning products. Coactive is a pioneering force in the machine learning landscape, and as an Applied Machine Learning Research Scientist, you’ll play a pivotal role in shaping the future of AI-driven solutions.

• Conduct in-depth market research to identify potential technological differentiators within the machine learning domain.
• Cultivate a culture of continuous learning and knowledge-sharing within the organization, fostering machine learning expertise and intuition.
• Serve as a key resource for cross-functional teams, providing expert insights and guidance on machine learning-related inquiries.
• Mentor and support fellow machine learning team members, promoting collaboration and skill development.
• Collaborate with clients and stakeholders to understand their challenges and co-create tailored machine learning solutions.
• Lead ideation and experimentation efforts to innovate and develop cutting-edge technologies for enhancing Coactive’s products.
• Build Machine Learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production, working closely with software engineers to assist in product ionizing your ML models.
• Perform hands‑on analysis and modeling of enormous data sets to develop insights.
• Run A/B experiments, gather data, and perform statistical analysis.
• Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation, and serving.
• Present findings and insights to senior leadership and at internal and external top scientific venues.

• PhD in Computer Science with a specialization in Machine Learning, showcasing expertise in cutting‑edge research and methodologies.
• Minimum of 2 years of experience in a similar role within a startup or research lab environment, demonstrating the ability to translate research into practical applications.
• Proven track record in machine learning, evidenced by publications in reputable conferences or journals.
• Strong proficiency in developing applications and algorithms based on the latest advancements in machine learning research.
• Familiarity with vector databases, leveraging their capabilities to enhance machine learning algorithms and applications.
• Hands‑on experience with the following programming languages:
  Python, Pytorch, Spark, Numpy, Scipy, Scikit‑Learn, VectorDB.

This is a…