EchoGlobal

Description:

We are looking for someone to join our team who is able and willing to develop a cold calling approach at EchoGlobal. You will speak with native English speakers in the USA, the UK, and Europe via cold calls. To be honest, we have not done this before. This opportunity is therefore suitable both for experienced candidates and for those with less experience who are eager to explore new ways of reaching new clients.

Our primary service is IT staff augmentation which is basically a type of recruitment for tech-oriented firms around the globe, additionally we offer traditional recruitment services. However, the market is currently very tough, so successfully securing even a few clients per year can be considered a very strong result.

Who are you?

• Comfortable and confident on the phone - you enjoy pitching and having conversations via phone.
• Target-driven and motivated by results. You consider every “No” as one step closer to a “Yes”.
• You analyze the outcome and change your approach when you see the need. 
• You like to research and test things - you use different opening lines and compare them to get the best results.

You have

• 1-2 years’ experience in outbound sales, BDR, SDR or business development of any kind in an IT related field.
• English level at least C1 (verbal predominantly).
• A tech-savvy mindset - it's not about writing code but about having a passion for technology, software, and automation.

What you will do

• Research and build targeted lead lists.
• Conduct outbound B2B sales calls, maintaining high daily call volumes (50 calls/day).
• Follow up with interested prospects via email or LinkedIn (if needed).
• Accurately enter, update and maintain all relevant information in Zoho CRM.
• Track calls analytics in Google Sheet and conversations in calling tools to analyze outcomes and performance.
• Participate in regular internal meetings (initially daily, later weekly).

Our values

1. Honesty & Integrity.
2. Responsibility.
3. Perseverance.
4. Ambition.
5. Initiative.
6. Cooperation & Teamwork.

Interviewing Stages

1. Test Task:

Record an audio which simulates a cold call that lasts up to 60 seconds. In this call, you must start with an opening line that grabs attention. During the call, imagine the prospect says, "OK, go ahead", and respond to it. You must also briefly explain our business service and value. Before ending the call, imagine the prospect says, "Sorry, we are not interested" and respond to that as well.

We guarantee feedback to everyone who sends us a link to the recording.

2. Interview with the CEO/COO.
3. Reference Check and Job Offer.

Company Description

#1 talent intelligence platform and global leader in recruiting software which serves over 125,000 recruiters around the world.

Project Description

You will work across backend, frontend, browser extension, and mobile surfaces to deliver real, user-facing impact. You will integrate AI/ML-powered features into workflows, own complex integrations, and help evolve a product used at scale. This role is product-focused, integration-heavy, and well suited for engineers who enjoy owning features end-to-end.

Requirments

• At least 5 years of experience as a full-stack engineer working with Rails and JS.
• Comfort building and consuming APIs, including GraphQL.
• Experience with complex integrations such as communications, payments, or third-party services.
• Solid understanding of relational databases and search systems.
• Product mindset with attention to UX, performance, and reliability.
• Ability to work effectively in an AI-augmented development environment.
• Excellent communication, analytical, and problem-solving skills.
• Advanced level of English.

Responsibilities

• Design and implement full-stack features using Ruby on Rails, GraphQL, and TypeScript/React.
• Integrate ML outputs into UI, search, and automations, working closely with AI and data teams.
• Build and maintain APIs consumed by web, mobile, and extension clients.
• Own feature quality including UX guardrails, edge cases, and observability.
• Contribute to scalable architecture across multi-region Kubernetes environments.
• Participate in code reviews, technical discussions, and iterative product delivery.
• Daily use of modern AI coding tools such as Cursor and Claude.

Technical Stack

Backend

• Ruby on Rails with Sorbet typing
• GraphQL and JSON APIs
• Background jobs, authentication, billing with Stripe
• Integrations with Google, Twilio, Intercom, Mailgun
• Postgres (PostGIS, pgvector), Redis, Elasticsearch

Frontend

• TypeScript and React
• Redux, Router, Relay
• MUI, Storybook
• Data visualization with Plotly or Recharts
• Mapping with Leaflet

Mobile

• React Native app using the same API surface as the web product

Infrastructure and DevX

• Kubernetes at scale, multi-region and multi-provider
• Strong observability with logging, metrics, and tracing
• Docker and devcontainers
• Local Minio S3, Postgres, Elasticsearch bootstrap
• CI-friendly workflows with RSpec or Minitest, Rubocop, Sorbet, Prettier

Working conditions

• Mon — Fri, 8h/day, overlap with US (CST) at least 4 hours.

Project

A platform reshaping the vehicle inspection market, allowing companies to run guided, computer vision–based inspections on any smartphone in just a few minutes, with AI assessing damage and estimating repair costs.

Role

Our client is looking for a Senior AI / ML Engineer to take ownership of improving the learning performance of AI models used for vehicle damage detection and damage size assessment. The role exists because the client’s current AI models have plateaued over the past year and they are looking for a fresh perspective to identify new approaches and drive further improvements in data, training, evaluation, and model design.

Qualifications

• 5+ years of experience in Computer Vision.
• Strong understanding of Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), and Convolutional Recurrent Neural Networks (RCNN).
• Experience working with large datasets.
• Strong programming skills in Python, TensorFlow, and PyTorch.
• Strong AWS experience (deployment, optimization).
• Usage of open-source CNN models such as Yolo.
• Bachelor’s degree in Computer Science or a related field.

Responsibilities

• Design, develop, and implement deep learning models using CNN, RNN, and RCNN for various applications.
• Work with large data sets to preprocess, clean, and prepare data for model training.
• Create datasets for training and testing.
• Train machine learning models and validate their accuracy, and deploy validated models into production.
• Optimize models for performance and accuracy, and fine-tune hyperparameters to achieve optimal results.
• Stay up to date with the latest developments in deep learning techniques and technology.
• Provide technical guidance and support to other team members.