I. About Landing AI
Landing AI, led by globally recognized AI leader Dr. Andrew Ng, is building cutting-edge vision products. We are at the forefront of creating domain-specific large vision models (LVMs) and the application of large multi-model models (LMMs) to practical vision tasks. Our Visual Prompting technology takes the ideas of text prompting and adapts them to vision – allowing vision models to be built not in hours, but in seconds. Moreover, our semantic vision layer enables businesses of all sizes to apply machine learning with minimal labeled data, turning images and videos into actionable insights. With our user-friendly tools, encapsulated in our LandingLens platform, we’re making visual AI accessible to developers worldwide.
II. Job Description
Location: Bay Area ideally or Seattle/Bellevue Secondarily.
About the Job:
Landing AI is working with some of the most sophisticated data science teams and AI-driven companies in the world on Domain-Specific Large Vision Models. Instead of scaling computer vision use cases linearly one by one, LVMs allow our customers to tackle downstream tasks in each domain by leveraging LVMs as foundation models and realizing significant value using vision agent frameworks. We are looking for a passionate ML Solution Engineer with a specialization in Machine Learning/Deep Learning and Computer Vision to join our dynamic team. This role is crucial not only in developing technical solutions but also in bridging the gap between technical capabilities and business goals through strategic sales and partnerships.
As an ML Solution Engineer at Landing AI, you will play a pivotal role in designing and implementing state-of-the-art vision-anchored solutions that solve real-world problems for our customers. Your expertise in machine learning/deep learning, combined with your understanding of sales processes and channel partnerships, will enable you to effectively align our solutions with customer needs and market demands. You will work closely with cross-functional teams, including product management, engineering, customer success, and sales/GTM, to ensure our solutions exceed customer expectations.
III. Responsibilities:
- Take ownership of Landing AI’s pre-sales relationships and help develop technical champions during the sales process for our prospects, customers, and partners.
- Engage with customers to understand their business challenges and technical requirements, and develop custom demos and tailored solutions that leverage Landing AI’s solution offerings.
- Lead client presentations, whiteboard sessions, and technical workshops, effectively communicating the value, differentiators and capabilities of our solutions.
- Led the design, development, and deployment of computer vision models and systems that address specific customer needs, ensuring performance, scalability, and reliability using Landing AI solutions.
- Utilize Docker and other containerization technologies to deploy machine learning models in a variety of environments, ensuring consistent, scalable, and efficient deployment.
- Collaborate with the sales team to articulate the technical and business value of our solutions, supporting sales presentations for both technical and executive audience, and proposal development.
- Collaborate with product and engineering teams to provide customer feedback, integrate machine learning models into our product suite, enhancing our offerings and competitive edge.
- Foster and expand partnerships with technology providers, OEMs, System Integrators (SIs), and industry organizations to enhance our technological capabilities and market presence.
- Stay abreast of the latest developments in machine learning and computer vision technologies, and incorporate cutting-edge techniques into our solutions.
- Provide technical guidance and mentorship to other team members, fostering a culture of excellence and continuous learning.
- Contribute to the development of project proposals, SOWs, white papers, blogs/articles, and case studies that showcase our expertise and success stories.
IV. Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a quantitative field, with a strong focus on machine learning preferably in deep learning (ideally computer vision).
- Demonstrated understanding of the sales process (MEDDIC) and experience working closely with sales teams to support and drive solution sales.
- Minimum of 5 years of relevant experience in developing and deploying machine learning models, with a proven track record in deep learning projects in a pre-sales or customer-facing capacity, preferably computer vision-related projects.
- Minimum of 2 years of relevant experience in cloud data warehousing solutions, preferably Snowflake.
- Outstanding communication and interpersonal skills, with the ability to articulate complex technical concepts to non-technical stakeholders.
- Experience in developing and maintaining strategic partnerships within the technology ecosystem.
- Demonstrated experience with model deployment either via REST API or containerization strategies such as Docker in various environments and architectures.
- Excellent problem-solving skills and a passion for innovation and continuous improvement.
- Ability to work independently and manage multiple projects simultaneously in a dynamic environment.
Preferred Qualifications
- Deep understanding of machine learning algorithms, deep learning frameworks (e.g., TensorFlow, PyTorch), and computer vision techniques (e.g., image recognition, OCR, object detection, segmentation, etc.).
- Demonstrated experience with cloud computing services (AWS, Google Cloud, and Azure) and machine learning deployment architectures.
- Strong programming skills in Python, JavaScript or C# and familiarity with software development best practices.
- Large multimodal/language model and agent framework experience is a plus.
- Linux experience is a plus.
V. Landing AI Benefits:
To be successful at Landing AI, you will have to fit well with our Landing AI Principles. Please take the time to read and understand them as they define who we are and what we look for in our candidates.
Although we are headquartered in Palo Alto, CA, We are open to remote workers in the U.S. as long as you are within a +3 hour time difference to the Pacific Time Zone (PDT / GMT -7).
