Machine Learning Solutions Engineer, Snorkel AI
Pre-Sales
Data-centric enterprise AI platform for
Job no longer available
Data-centric enterprise AI platform for
101-200 employees
Job no longer available
101-200 employees
Company mission
To empower everyone to solve their most impactful problems through data-centric AI.
Role
Who you are
- 2+ years of experience in customer facing technical roles (can include sales at a B2B software company or DS/ML consulting)
- Experience executing a value centric sales motion using MEDDPIC, Command of the Message or other value centric sales methodologies and qualification frameworks
- Expertise in modern machine learning frameworks and technologies (e.g. PyTorch, TensorFlow, transformers)
- Knowledge of industry standard technologies in the Data Science and Machine Learning space
- Fluency with scripting in Python
- Hands-on experience building and implementing machine learning or AI models
- Experience collaborating with business stakeholders to ensure that machine learning solutions deliver successfully on business outcomes
- Outstanding presentation skills to both technical and executive audiences, whether impromptu on a whiteboard or using presentations and demos
- Ability to connect a customer's specific business problems to Snorkel’s differentiated platform and unique approach to ML development
- University degree in computer science, engineering, mathematics or related fields, or equivalent experience preferred
What the job involves
- Snorkel AI is enabling a paradigm shift in ML development by helping organizations take a programmatic approach to machine learning application development. In support of our growth, we are recruiting a high caliber founding team of ML solution engineers to join our fast growing GTM team.
- In this role, you will act as a trusted advisor to prospective and existing customers. You will also work directly with our co-founding team, sales team, product team and ML Engineering team to provide value-based evaluation scenarios including demonstrations, labs, and POVs, to aid in closing business.
- 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
- Machine Learning Solution Engineers own the technical aspects of the sales cycle, designing and leading a tailored and business value-aligned technology evaluation process
- Serve as our first line expert educators on the Snorkel Flow Platform, building demos and presentations for customers and field experts
- Act as the primary customer-facing technical resource during customer / partner meetings and technology evaluations, working at all levels in the organization with Data Scientists, AI/ML practitioners, Architects, Technologists, Product owners, Transformation leaders, LOB & C-level executives
- Serve as a trusted advisor on AI to help customers with their end-to-end vision; AI strategy, operating model & architectural best practices, problem framing, data preparation, scripting, model building, model deployment, model management, and output consumption
- Partner with sales leadership to achieve quota targets while also ensuring our customers are well positioned for a successful hand-off to our post-sales and customer success teams
- Provide guidance to revenue leaders on sales strategy, product obstacles/gaps and represent the team's needs to executive staff
- Interpret complex problems, create simple solutions and collaborate closely with prospects, channel partners and our sales team to deliver winning solutions that help customers to accelerate critical business outcomes with AI
- Collaborate and maintain a close working relationship with our co-founders, product, engineering, sales, and marketing
- Systematize and playbook pre-sales activities, such as demo and POC assets
Our take
Demand for AI is increasing in almost every industry, but the machine learning that fuels it is tedious to set up. In order to train machine learning algorithms, training data must be labelled manually, and this contributes to expenses in time, money and resources when integrating AI within a business.
Snorkel AI develops programmatic approaches to data labelling in order to automate the setup process of machine learning and decrease the required timeframe for a business to begin providing AI services. In addition to these automated data categorization services, the company also integrates data training, management, and analysis into a unified AI-deployment platform.
The complex computer science behind AI setup has resulted in many businesses without computer science backgrounds being left behind, and Snorkel AI has set this as their target audience. As of 2023, this customer base has tripled in size since Snorkel AI's founding and in 2024, enjoyed a new round of funding. With these promising developments, the company continues to innovate the sector.
Kirsty
Company Specialist at Welcome to the Jungle
Company
Funding (last 2 of 3 rounds)
Aug 2021
$85m
SERIES C
Apr 2021
$35m
SERIES B
Total funding: $135m
Company benefits
- Home office allowance
- Yearly wellness stipend
- Healthy meals, snacks & drinks in office
- 401k with a 100% match up to 5% of annual salary
- Regular team events
- Generous paid parental leave
- Work from home opportunities
- Health insurance
Company HQ
Centennial, Redwood City, CA
Leadership
Alex Ratner
(Co-founder & CEO)Studied at Harvard and received a PhD from Stanford. They are also an Assistant Professor at the University of Washington.
Paroma Varma
(Co-founder)They hold a PhD from Stanford and was VP of Corporate Relations at the Society of Women Engineers. They have collaborated with teams at Facebook and Intel.
Braden Hancock
(Co-founder & Head of Technology)They have a PhD in Computer Science from Stanford, and worked as a Research Assistant with the Air Force and MIT. They were also a Software Engineer at Google, and a Researcher at Facebook.
Henry Ehrenberg
(Co-Founder)They studied at Yale and Stanford and worked at Facebook as a Quantitative Engineering Intern and a Senior Applied Research Scientist.
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