Senior Sales Engineer, Data Science
vor 3 Monaten
Senior Sales Engineer, Data Science & Machine Learning 1 days ago
Description About The Company: With a $100B market opportunity that's growing rapidly, Wallaroo.AI is standing at the forefront of enabling data scientists, AI teams, and ML engineers to get from AI prototype to ROI in production with incredible efficiency, scale, and ease.
Wallaroo.AI removes infrastructure bottlenecks and allows AI teams to deliver real-world results faster, so technical teams can reclaim 40% of their time, reduce infrastructure costs by as much as 80%, and get-to-value 3X faster - in any cloud, on-prem, or edge environment.
Our enterprise platform provides powerful self-service tools, a purpose-built inference server for ML workflows, observability, and an A/B testing framework.
We're already working with some of the world's leading brands.
Backed by Microsoft's M12, we raised a $25MM Series A in 2022.
The time is NOW, join us on this incredible journey
About You & Your Role: As one of the earliest members of Wallaroo.AI's Sales Engineering team, you will lean on your past (or current) customer-facing experience with data science or machine learning-related products (or your past life as a data scientist or machine learning engineer) to solve meaty problems for our clients.
You'll play a critical role in driving successful pre-sales engagements with prospects and customers as an integral part of our overall enterprise sales motion.
At the same time, you will act as the voice of the company and spokesperson at events, meetups, and other communities, while influencing the roadmap and GTM decisions, infusing customer priorities into every decision we make.
You are curious and an avid learner who believes in continuous improvement, collaboration, and always putting the customer first.
You have deep experience in a customer-facing role, such as Sales Engineering, Solution Architecture, Customer Success Engineering, or Consulting (with a highly technical product), and you have the tech chops to communicate with Data Science and ML Engineering leadership.
Either way, you ask the right questions to quickly understand the customer's Machine Learning/AI Workflows and pain points and you articulate clearly and concisely the best possible technical solutions.
Most of all, you care about the customer's success and in seeing the value of the Wallaroo.AI solution when applied to their enterprise.
You will be expected to own the technical side of relationships with Data Science/Machine Learning Engineering leadership at prospective clients, be diligent and detail-oriented in guiding them from technical discovery through structuring and executing an evaluation or proof of concept.
Because Wallaroo.AI has aggressive growth plans, you will be expected to leverage your skills and experience to aid in building the shared knowledge base and company-wide assets, pulling in relevant stakeholders (Founders, Engineering, Product, Marketing, etc.)
as necessary, so the entire team is aligned on overcoming challenges.
Your success will be measured by how efficiently you can demonstrate real value to the prospects in a timely manner.
This will often mean applying your critical thinking skills to solve open-ended problems in a way that meets requirements and gives prospects the best possible experience while staying organized to effectively support multiple opportunities in parallel.
Must Haves: Bachelor's level degree or higher in Computer Science, Data Science, or related field, or significant experience and proficiency in Python.
3 or more years of experience in a customer-facing technical sales/services capacity or 3 or more years of experience building machine learning models for internal or external stakeholders.
Success working in an early-stage environment, where you have helped build processes from scratch when there is ambiguity and where you've had the autonomy to own and execute on projects.
Deep experience writing code in Python, including:Strong proficiency with common data processing libraries such as pandas and numpy.
At least 2 years of experience working with various ML models, frameworks, and libraries, namely Tensorflow, PyTorch, Scikit-Learn, XGBoost, and HuggingFace.
Strong experience in technical project management, and the ability to plan out and execute on multiple simultaneous projects in a highly organized fashion, treating customer requests as your priority, providing top-tier service throughout the opportunity, and ensuring they make forward progress in a timely manner.
Excellent verbal and written communication skills; you're able to take complex technical ideas and distill them down to core points and impact while simultaneously building relationships with customers and prospects as a trusted technical advisor.
Entrepreneurial: Self-motivated and resourceful (Creative, Bold, Risk Taking) with the grittiness to roll up your sleeves and work collaboratively to find creative solutions to hard problems.
Gold Stars: Experience working in the MLOps ecosystem.
Experience working in AWS, GCP, and Azure.
Familiarity with corporate/cloud networking tools and concepts.
Proficiency with common open-source technologies for orchestration and deployment (Docker, Kubernetes, Helm).
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