Software Engineer (Sales & CS)

Neurolabs
London
8 months ago
Applications closed

Related Jobs

View all jobs

Software Engineer / Computer Science Placement

Software Engineer (Python React)

Software Engineer Lead

Software Engineer - Medical Device

Software Engineer - £50,000 - £65,000 per year - Dorset

Software Engineer

Neurolabsis seeking a talentedSoftware Engineerto join our Sales & Customer Success team. We specialise in democratising Computer Vision technology, making it accessible to businesses of all sizes. With a commitment to pushing boundaries and solving complex problems, we have built a reputation for excellence in the retail automation industry.

Employment type:Full-time, permanent contract

Experience:Mid and Senior level

Annual Salary:£60,000 - £80,000

Role Overview:

As a Software Engineer in the Sales & CS department at Neurolabs, you will play an instrumental role in developing and managing our internal tooling, ensuring seamless delivery of projects to our diverse client base. You will collaborate closely with our product & machine learning teams to streamline implementation processes as well as automate the deployment & maintenance of our cutting-edge machine learning solutions, enhancing the overall efficiency of our operations. Your work will directly impact the efficiency and success of our project implementations, while also playing a crucial role in understanding and fulfilling both internal & external stakeholder needs.

The role offers the chance to be part of a team delivering complex solutions to enterprise clients, giving you exposure to both cutting edge AI and applying these to solving real world problems.

Responsibilities

Tool Development & Management:

  • Design, develop, and maintain robust internal tools to streamline project delivery processes.
  • Ensure the tools are scalable, reliable, and easy to use for the delivery team.
  • Implement automation and optimisation strategies to improve efficiency.

Project Delivery:

  • Collaborate with project managers and the delivery team to understand project requirements and objectives.
  • Customise and configure tools to meet specific project needs and client requirements.
  • Troubleshoot and resolve any technical issues that arise during project implementation.

Cross-functional Collaboration:

  • Engage with internal stakeholders to gather requirements and feedback for tool improvements.
  • Translate stakeholder needs into technical specifications and actionable development tasks.
  • Maintain regular communication with stakeholders to ensure alignment and satisfaction.
  • Provide technical support to the sales team, including troubleshooting and issue resolution.

Quality Assurance:

  • Conduct thorough testing of internal tools to ensure high quality and performance.
  • Implement best practices for code quality, documentation, and version control.

Continuous Improvement:

  • Stay up-to-date with industry trends and best practices
  • Propose and implement innovative solutions to enhance our service delivery capabilities.

Requirements

  • Education & Experience:
    • Bachelor’s degree in Computer Science, Software Engineering, or a related field.
    • 4+ years of experience in software development, preferably within a startup or dynamic environment.
  • Technical Skills:
    • Proficiency in programming languages such as Python, JavaScript, or similar.
    • Experience with cloud platforms (e.g., AWS, Azure), API Integrations & data engineering best practices.
    • Experience with web development frameworks (e.g., Streamlit, React, Angular, or equivalent)
    • Familiarity with computer vision frameworks and libraries is a plus.
    • Good understanding of databases and data management systems.
    • Experience with sales and customer success tools/systems (e.g., CRM, ticketing system) is a plus
  • Soft Skills:
    • Strong problem-solving abilities and a proactive approach.
    • Excellent communication skills to collaborate effectively with team members and stakeholders.
    • Ability to work independently and manage multiple tasks in a fast-paced environment.

Benefits

  • Pension Plans
  • Work From Home - minimum 2 days in the office per week
  • Flexible working hours from home or our offices in Edinburgh or London
  • Equity options
  • 34 days annual leave (incl. public holidays in your residence country)
  • Bi-annual company retreat and bi-annual team meetings (workation)
  • Private medical insurance, including mental health, dental, opticians cover, and business as well as personal travel insurance.
  • Cycle to Work Scheme

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Navigating AI Career Fairs Like a Pro: Preparing Your Pitch, Questions to Ask, and Follow-Up Strategies to Stand Out

The field of Artificial Intelligence (AI) is growing at an astonishing pace, offering a wealth of opportunities for talented professionals. From machine learning engineers and data scientists to natural language processing (NLP) specialists and computer vision experts, the demand for skilled AI practitioners continues to surge in the UK and globally. AI career fairs present a unique opportunity to connect face-to-face with potential employers, discover cutting-edge innovations, and learn more about the rapidly evolving landscape of data-driven technologies. Yet, attending these events can feel overwhelming: dozens of companies, queues of applicants, and only minutes to make a great first impression. In this detailed guide, we’ll walk you through strategies to prepare for AI career fairs, provide you with key questions to ask, highlight examples of relevant UK events, and reveal the critical follow-up tactics that will help you stand out from the crowd. By the end, you’ll be armed with the knowledge and confidence to land your dream role in the ever-growing world of Artificial Intelligence.

Common Pitfalls AI Job Seekers Face and How to Avoid Them

The global demand for Artificial Intelligence (AI) specialists continues to rise, with organisations across industries keen to implement machine learning, deep learning, and data-driven insights into their operations. Yet, as the market for AI professionals flourishes, so does the level of competition among candidates. Talented individuals who may otherwise be qualified often stumble on common pitfalls that can hinder their success in securing an AI-related role. These pitfalls can lie in their CV, interview approach, job search strategy, or even their understanding of what AI employers are looking for. This article aims to help job seekers in the UK’s AI sector—whether you’re fresh out of university, transitioning into AI from another field, or looking for a senior-level position—avoid the most common mistakes. We’ll discuss how to stand out in a crowded AI job market by improving your CV, acing interviews, and conducting an effective job search. Read on to discover the typical missteps AI professionals make when seeking employment and learn the strategies to avoid them.

Career Paths in Artificial Intelligence: From Research to Management – How to Progress from Technical Roles to Leadership and Beyond

Artificial Intelligence (AI) stands at the forefront of technological innovation, shaping everything from healthcare diagnostics to autonomous vehicles and natural language processing. With the UK widely recognised as a growing hub for AI research and development, there has never been a better time to explore a career in artificial intelligence—or to advance your current trajectory within the field. A key question that often arises is: How can professionals move from hands-on technical roles in AI to leadership and management positions? This comprehensive guide will walk you through the evolving career landscape in AI, from entry-level posts to executive roles. We will examine in-demand skills, recommended pathways for professional development, and strategies to help you seamlessly ascend from technical responsibilities to strategic leadership. Whether you’re a recent graduate, a self-taught data whizz, or an experienced machine learning engineer aspiring to lead teams, this article will provide you with practical insights tailored to the UK’s vibrant AI sector.