Nearly half of the generative AI job postings in the past year were for roles in San Francisco, San Jose, New York, Los Angeles, Boston, and Seattle. These six AI hotspots have been identified by the Brookings Institution, which also found that San Francisco is home to 20 of the best-funded AI companies, a figure that’s more than the rest of the U.S. combined. California is home to 35 of Forbes’ AI 50 companies, with the Bay Area and, in particular, San Francisco and San Jose, comprising 60% of new generative AI jobs as of May 2023. The poster-child for generative AI, OpenAI — the founder of ChatGTP — is located here. New York houses four top-50 AI companies, Texas is home to two, and Massachusetts has one.
The AI Landscape in Key Cities
In New York, image and video editing company Runway, founded in 2018, has a suite of 30 AI-powered tools, which were actually used for some scenes in the Oscar-winning Everything Everywhere All at Once. The Boston-based Path AI assists in the work of pathologists by scanning tissue samples using artificial intelligence, providing analysis via color coding — cancer is red, and dead cells are black, for example.
With funding for AI companies ramping up, more than one in four dollars invested in American startups this year has gone to an AI sector company according to Crunchbase. This is twice what it was a year ago, and it seems apparent that this larger share of investment in AI is going to continue. So, if you’d like to capitalize on your existing skills in a growth sector, then the VentureBeat Job Board should be your first stop. You can find thousands of openings across hundreds of fields.
Opportunities in the AI Sector
“Arthur is deeply passionate about building technology to make AI understandable, effective, and fair.”
– VentureBeat Job Board
The Solutions Engineer will work with some of the world’s most innovative companies to help deploy fair, safe, and reliable ML systems. You’ll partner with sales to identify technical problem statements that impact clients’ AL/ML initiatives, engage with data scientists, model owners, line-of-business executives, and other related personas to unpack AI problem statements and deliver high-impact business outcomes.
- Five or more years’ experience in sales engineering, solutions engineering, or similar relevant experience with enterprise software products.
- Solid experience with software product demonstrations, technical deep-dive presentations, and technical objection handling.
Apply for this job now.
“WWT was founded in 1990 in St. Louis, Missouri and employs over 9,000 people, with more than $17 billion in revenue in 2022.”
– VentureBeat Job Board
As Technical Solutions Architect II – AI Security, you’ll have proven experience with selling solutions internally or directly to customers, expertise in machine learning, natural language processing, and other AI technologies, and knowledge of common AI/ML frameworks like TensorFlow, PyTorch, scikit-learn, OpenCV, etc.
- An understanding of AI security vulnerabilities and mitigation strategies like adversarial machine learning, data poisoning, and model extraction.
- Demonstrated experience with software security, secure coding, or software assurance tools and techniques.
- Hands-on experience implementing AI/ML technologies for security use cases like threat detection, user behavior analysis, and identity verification.
See all the requirements here.
“Snorkel AI is redefining how people and organizations build AI applications.”
– VentureBeat Job Board
In the role of Machine Learning Solutions Engineers, you will act as a trusted advisor to prospective and existing customers. You will sit at the intersection of product, sales, and engineering and will work with the broader team to continue building Snorkel Flow into the leading platform for data-first AI, owning the technical aspects of the sales cycle, designing and leading a tailored and business value-aligned technology evaluation process, and serving as a first-line expert educator on the Snorkel Flow Platform, building demos and presentations for customers and field experts.
- Two years’ of experience in customer-facing technical roles.
- Expertise in modern machine learning frameworks and technologies.
- Knowledge of industry-standard technologies in the data science and ML space.
- Fluency with scripting in Python.
Find out more now.
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