Growth Executive

Salary

₹15 - 20 LPA

Min Experience

1 years

Location

Bangalore

JobType

full-time

About the role

Overview

Company name: Simplismart | HQ Location: San Francisco | Website | LinkedIn

Role: Growth Executive

  • Salary: Rs. 15-20 lakhs per year
  • Experience: 1-4 years
  • Location: Bangalore
  • Type: Full-time

We are seeking a talented and driven Growth Associate with expertise in Inbound Sales to join our team in Bangalore. In this role, you will be responsible for converting inbound leads into long-term customers by understanding their needs and providing tailored solutions.

Key Responsibilities:

  1. Respond promptly to inbound leads and inquiries, qualifying prospects based on their needs and fit.
  2. Nurture relationships with potential customers, guiding them through the sales funnel.
  3. Collaborate with the marketing team to refine lead qualification criteria and improve conversion rates.
  4. Conduct product demonstrations and presentations to showcase value to prospects.
  5. Maintain accurate records of interactions, sales progress, and customer information in CRM systems.
  6. Meet and exceed sales targets while contributing to team goals.

Required Skills & Experience:

  1. Proven experience in inbound sales or a related role, with a strong track record of meeting or exceeding targets.
  2. Excellent communication, presentation, and interpersonal skills.
  3. Ability to quickly understand customer pain points and articulate solutions effectively.
  4. Proficiency in using CRM tools and sales software.
  5. Strong problem-solving skills and a customer-focused mindset.

Preferred Qualifications:

  1. Experience in [specific industry/domain, if applicable].
  2. Familiarity with [specific tools, if applicable, e.g., HubSpot, Salesforce].
  3. Bachelor's degree in business, marketing, or a related field.

About the company

About us
Fastest inference for generative AI workloads. Simplified orchestration via a declarative language similar to terraform. Deploy any open-source model and take advantage of Simplismart’s optimised serving. With a growing quantum of workloads, one size does not fit all; use our building blocks to personalise an inference engine for your needs.

API vs In-house

Renting AI via third-party APIs has apparent downsides: data security, rate limits, unreliable performance, and inflated cost. Every company has different inferencing needs: One size does not fit all. Businesses need control to manage their cost <> performance tradeoffs. Hence, the movement towards open-source usage: businesses prefer small niche models trained on relevant datasets over large generalist models that do not justify ROI.

Need for MLOps platform

Deploying large models comes with its hurdles: access to compute, model optimisation, scaling infrastructure, CI/CD pipelines, and cost efficiency, all requiring highly skilled machine learning engineers. We need a tool to support this advent towards generative AI, as we had tools to transition to cloud and mobile. MLOps platforms simplify orchestration workflows for in-house deployment cycles. Two off-the-shelf solutions readily available:

  1. Orchestration platforms with model serving layer: do not offer optimised performance for all models, limiting user’s ability to squeeze performance
  2. GenAI Cloud Platforms: GPU brokers offering no control over cost

Enterprises need control. Simplismart’s MLOps platform provides them with building blocks to prepare for the necessary inference. The fastest inference engine allows businesses to unlock and run each model at performant speed. The inference engine has been optimised at three levels: the model-serving layer, infrastructure layer, and a model-GPU-chip interaction layer, while also enhanced with a known model compilation technique.

Skills

inbound sales