Programmer/Analyst, Ship With Amazon

Amazon
London
1 month ago
Applications closed

Related Jobs

View all jobs

Trainee Data Analyst Programme (Hiring Immediately)

Data Analyst Placement Programme - Accredited Online Training (Hiring Immediately)

Data Analyst Placement Programme - Seamless entry into the data analysis sector (Hiring Immediately)

Data Analyst Placement Programme (Hiring Immediately)

Data Analyst Placement Programme - Accredited Online DA Training (Hiring Immediately)

Data Analyst Placement Programme (Hiring Immediately)

Amazon’s global fulfillment network enables any merchant to ship items that are ordered on Amazon to any place on earth. There is a complex network of ways in which items move between vendor locations, Amazon warehouses, and customer locations as well as several intermediate locations through which packages travel before reaching the customer. With a scale of millions of packages, each with different attributes and delivery requirements, what results is a highly dense graph of nodes.

We have built a highly respected software engineering team which is focused on solving complex problems in worldwide transportation using workflows, optimization algorithms, and machine learning systems. These are large-scale distributed systems handling millions of packages being shipped through the Amazon logistics network.

We are looking for a software programmer analyst who will be responsible for working with business and collaborate with technology teams to integrate new methods into the network. As part of the integration, you have to design, develop and maintain software projects, updating/enhancing our current software, automation of manual configuration processes and documentation of our systems.

Your solutions will impact our customers directly! This job requires you to be able to learn and work on disparate and overlapping tasks.

BASIC QUALIFICATIONS

  1. B.Tech in Computer Science or a related field.
  2. 3+ years overall development/technical support experience.
  3. Strong object oriented development knowledge in C++ and/or Java.
  4. Knowledge of the UNIX/Linux operating system.
  5. Ability to understand functional/technical specifications and analyze data.
  6. Proven ability to troubleshoot and identify the root cause of issues.
  7. Demonstrates skill and passion for operational excellence.
  8. Documentation skills.

PREFERRED QUALIFICATIONS

  1. B.Tech in Computer Science or a related field.
  2. 3+ years overall development/technical support experience.
  3. Strong object oriented development knowledge in C++ and/or Java.
  4. Knowledge of the UNIX/Linux operating system.
  5. Ability to understand functional/technical specifications and analyze data.
  6. Proven ability to troubleshoot and identify the root cause of issues.
  7. Demonstrates skill and passion for operational excellence.
  8. Documentation skills.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visitthis linkfor more information.

Posted:March 13, 2025 (Updated about 2 hours ago)

Amazon is an Equal Opportunity Employer – Minority / Women / Disability / Veteran / Gender Identity / Sexual Orientation / Age.

#J-18808-Ljbffr

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.

Jobs

Portfolio Projects That Get You Hired for Machine Learning Jobs (With Real GitHub Examples)

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!

Jobs Careers

Machine Learning Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.

Jobs

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.