ML Research Engineer (San Jose)

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. 

As an ML Research engineer, you will work coactively with the best in ML and data systems, building the foundation for understanding unstructured image and video data.

What you’ll do:

• Solve complex machine learning problems in the multimodal space to support retail, media and entertainment use-cases.
• Collaborate with a world-class team of engineers, researchers, and scientists to create algorithms built on top of machine learning models to enable efficient, scalable search and analysis on large scale unstructured data.
• Perform literature research, design and conduct experiments, benchmark algorithm performance and scalability.
• Continuously improve algorithm performance to outperform open source state of the art.
• Mentor  the team by advocating to shape engineering best practices and company culture as we grow.

What we look for:

• BS (or higher) in Computer Science or related fields, or equivalent experience.
• Experience with Computer Vision, Natural Language Processing (NLP), and/or Audio Processing is highly preferred.
• 5+ years experience writing production-grade code in Python, Java, C++, or similar language.
• 5+ years experience building application software on cloud native platforms (AWS, Azure or GCP). Experience building enterprise applications is a plus.
• Experience building and maintaining pipelines for large scale ML training, monitoring, and serving (PyTorch, Tensorflow, TFX).
• Experience in developing efficient data-intensive algorithms.
• Please note that periodic travel to the United States is required

What you can expect from us:

This is a hybrid work environment based in San Jose, CA (3 days in the office).

The opportunity to work on cutting-edge projects with a team of world-class engineers and researchers.

The estimated annual base salary is between $185,920 and $212,800.* 

At Coactive, cash salary is only one part of our total compensation package. Other benefits for this position include, but are not limited to

• 100% medical, dental & vision coverage for you
• Medical, dental & vision partially covered for your dependents
• Unlimited PTO
• A supportive environment. We build products, but we develop people.
• Social events ranging from happy hours and hiking to board game nights and games of Mario Kart.

Further, you can expect a supportive work environment from us. We build products, but we develop people. 

Join us in revolutionizing how businesses harness the power of machine learning to unlock the potential of unstructured data. If you're passionate about driving innovation, then we'd love to have you on board.

 

*Actual pay is dependent on an individual candidate’s professional background, experience, skills and qualifications, as well as market demand and business demands.