Account Executive

Overview

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

Role: Account Executive

• Salary: Rs. 20-30 lakhs per year
• Experience: 2-6 years
• Location: Bangalore
• Type: Full-time

We are seeking a results-driven Account Executive with expertise in B2B Sales to join our team in Bangalore. In this role, you will identify and engage with potential clients, nurture relationships, and close deals that contribute to our company's success.

Key Responsibilities:

1. Develop and execute strategies to identify, qualify, and close new business opportunities.
2. Build and maintain strong relationships with clients to understand their needs and offer tailored solutions.
3. Manage the entire sales cycle, from lead generation to deal closure.
4. Collaborate with internal teams to ensure smooth delivery of products/services to clients.
5. Achieve and exceed sales targets while contributing to team goals.
6. Maintain accurate records of sales activities and customer interactions in CRM tools.

Required Skills & Experience:

1. Proven experience in B2B sales, with a strong track record of meeting or exceeding sales targets.
2. Excellent communication, negotiation, and relationship-building skills.
3. Ability to understand client needs and translate them into effective solutions.
4. Proficiency in CRM tools and sales management software.
5. Strong problem-solving skills and a results-oriented mindset.
   
   

Preferred Qualifications:

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

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.