Sales Engineer (AI/ML)
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 a Customer engineer with a specialization in machine learning, you will be the linchpin bridging sales, customer success, and engineering. Your primary goal is to address customers’ critical needs through our cutting-edge ML technologies while emphasizing exceptional customer service. Collaborating closely across multiple teams, you’ll champion the adoption of Coactive’s products and ensure seamless integration into our clients’ workflows.
Responsibilities:
- Provide comprehensive technical support to sales and customer success, establishing a robust feedback loop for product enhancement
- Develop and deliver top-tier technical content tailored for enterprise clients (e.g., video tutorials, sector-specific demonstrations, documentation, etc.)
- Lead and execute successful Proof-of-Value engagements for clients
- Plan and conduct technical workshops for both existing and prospective clients
- Act as a liaison among internal teams, advocating for prospects, and relaying valuable insights gathered from field engagements
- Maintain meticulous documentation and streamlined processes to facilitate efficient collaboration
- Occasional travel to customer sites and industry conferences may be required
Qualifications:
- Bachelorβs degree (or higher) in Computer Science or related fields, or equivalent professional experience
- Over 2 years of practical experience as a Machine learning engineer
- Proficiency in data infrastructure and ML tools like PyTorch, TensorFlow, scikit-learn, MLflow, Spark, and Ray
- Demonstrated experience providing technical guidance and support in customer calls & interactions, addressing product usage needs, and resolving issues
- Track record in developing pre and post-sales materials; eagerness to mentor and educate fellow Solutions Engineers and Account Executives
- Ability to navigate clients toward value-driven solutions, enhancing enterprise product usage.
- Proficiency in creating tools for non-technical teams and adapting to a rapidly evolving startup environment
- Minimum of 2+ years of customer-facing enterprise sales experience
- Proficiency with coding languages Python, Java, C++, or similar languages at a production level
Additional Information:
This is a hybrid position based in San Jose, California. The estimated annual base salary for this position is between $125,000-$156,000 . At Coactive, cash salary is only one part of our total compensation package. Other benefits for this position include, but are not limited to: Market leading equity grants, 100% medical, dental, & vision coverage for you, Medical, dental, & vision partially covered for your dependents, Unlimited PTO, Social events ranging from book clubs, 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
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