Back to Jobs

Sales Engineer

NanoNets
CA, US, Seattle, WA, US, Remote (CA, US; WA, US; TX, US)
Full-time
$125K–$157K
Estimated
Remote
Apply Now

Required Skills

Machine Learning
Python
R
Typescript
Go
Tensorflow
Pytorch
React
Sql
Mysql
Cassandra
Aws
Gcp
Kubernetes
Jenkins
Research
Communication

Job Description

Nanonets is automating document information extraction using AI. We are headquartered in San Francisco. We are backed by prestigious investors from bay area like Y-Combinator, SV Angels, Sound Ventures by Ashton Kutcher. We are currently profitable and growing at a fast pace and looking to expand our team. We are building a product that lets companies automate extracting key information from documents like invoices, receipts, or any other kind of document and integrate it into their workflows saving manual work. We need to keep building features that will let users automate millions of documents of different kinds every day, feed them to our AI for learning, plug our API to external systems like salesforce, quickbooks, RPA providers etc. You should check it out at https://app.nanonets.com Nanonets is a SAAS product that automates manual processes for other companies. We use state-of-the-art machine learning algorithms to enable this hyper-automation. We are looking for our first Sales Engineer to work closely with our sales team (In US timezone) and assist them in selling this technical product to other companies. A big part of the role will be to understand Nanonets product really well, understand customer requirements/goals and build machine learning models on the Nanonets platform to demo capabilities to customers on their own data. This would be instrumental in helping close sales faster. If you are interested in AI/ML space, good with communication, enjoy tasks with quick wins and love solving on diverse set of problems, this role would be good fit for you. Responsibilities: Accompanying salespeople on client calls to answer technical questions, understand their current processes and goals with Nanonets, and suggest improvements. Building solutions/demos based on their requirements using Nanonets product Solving challenges potential customers might be facing with the product Researching about customers current tools/stack and building technical architecture for end solution we are proposing that will solve their problem Thinking of applying? Try our resume builder— it's free, fast, and tailored to help you stand out. Some of the interesting things our backend team has shipped Compile python code into C which could be imported into golang and then shipped as binary for on premise systems Autoscale GPU dependent services with kubernetes with a custom metric Displaying machine learning metrics in simplified ways to end users so they can act based on those metrics Building large number and variety of integrations with relatively generic interface like salesforce, quickbooks, RPA's, external databases Process large number of files in highly distributed manner in golang Compile python code into C which could be imported into golang and then shipped as binary for on premise systems Autoscale GPU dependent services with kubernetes with a custom metric Displaying machine learning metrics in simplified ways to end users so they can act based on those metrics Building large number and variety of integrations with relatively generic interface like salesforce, quickbooks, RPA's, external databases Process large number of files in highly distributed manner in golang Some of the interesting things our frontend team has shipped Ability for users to annotate documents so AI can learn which fields to extract Displaying machine learning metrics in simplified ways to end users so they can act based on those metrics Letting users build complex visual workflows around our API in our product. Let users visualize complex ML metrics in a very simple and intuitive way Ability for users to annotate documents so AI can learn which fields to extract Letting users build complex visual workflows around our API in our product. Let users visualize complex ML metrics in a very simple and intuitive way Our stack: Databases Cassandra DB Postgres/MySQL Backend Golang for API and other microservices Python for Machine learning (Tensorflow, Pytorch) Frontend React, Typescript Mobx Cloud Providers AWS GCP for ML heavy workload Monitoring/Alerting ELK for logging Prometheus for Monitoring Graphana for dashboards Orchestration Kubernetes DevOps Jenkins for CI/CD Databases Cassandra DB Postgres/MySQL Cassandra DB Postgres/MySQL Cassandra DB Postgres/MySQL Backend Golang for API and other microservices Python for Machine learning (Tensorflow, Pytorch) Golang for API and other microservices Python for Machine learning (Tensorflow, Pytorch) Golang for API and other microservices Python for Machine learning (Tensorflow, Pytorch) Frontend React, Typescript Mobx React, Typescript Mobx React, Typescript Mobx Cloud Providers AWS GCP for ML heavy workload AWS GCP for ML heavy workload AWS GCP for ML heavy workload Monitoring/Alerting ELK for logging Prometheus for Monitoring Graphana for dashboards ELK for logging Prometheus for Monitoring Graphana for dashboards ELK for logging Prometheus for Monitoring Graphana for dashboards Orchestration Kubernetes Kubernetes DevOps Jenkins for CI/CD Jenkins for CI/CD Screening Call - 1 hour call This is a screening call to learn more about the role and see if it's a good fit. We will also conduct a live Python coding round. Sales screen - 1 hour This round is to assess your communication skills and fit to work in a sales engineering role. This round will be taken by our CTO & Co-Founder. You will need to have understanding of Nanonets in some details for this round. F2F Meeting - 1 Day Meet our co-founders in our SF Bay Area office as a final round of conversation

Job Details

Employment Type

Full-time

Salary Range

$125K–$157K

Estimated

Location

CA, US, Seattle, WA, US, Remote (CA, US; WA, US; TX, US)

Remote Work

Remote Friendly