Snr Consultant AI/ML, Tech & Industry

Amazon
London
1 month ago
Applications closed

Related Jobs

View all jobs

Senior Project Engineer

Job ID: 2789017 | Amazon Web Services Singapore Private Limited

AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector.

AWS Asia Pacific & Japan (APJ) Professional Services (ProServe) is seeking for a Senior Consultant, AI/ML for its Technology & Industry team. This role will be focused on helping customers build or migrate their data-driven business workloads on AWS.

From ideation through to build and then to operate, AWS ProServe is committed to helping customers accelerate their time-to-value. AWS ProServe engages in a wide variety of customer projects, providing collective AWS experience, best practices, and technical skills for the Customer. Our team collaborates across the entire AWS organization to bring access to product, service, and training teams, to deliver the right solutions and drive feature innovations for our customers across all industries.

This Senior Consultant will be based in Singapore but have an APJ wide remit in the Professional Services team. Successful candidates will be experienced and motivated business-oriented AI/ML practitioners. They must possess a unique balance of business knowledge and Technology depth in Artificial Intelligence and Machine Learning with delivery implementation experience. Their focus will be on providing pre-sales support with customer executives followed by hands-on-delivery for AI ML workloads.

Successful candidates will have executive level experience in leading, defining, designing and deploying enterprise level strategic solutions leveraging Data, Artificial Intelligence and Machine Learning. Domain expertise should include deep, practical and hands-on understanding of Machine Learning, Data and Business intelligence. The ideal candidate will also have experience with managing data at scale and automation.

Key job responsibilities

  1. Innovate – Engage with the customer’s business and technology stakeholders to create a compelling vision of a data-driven enterprise in their environment.
  2. Deliver value – Lead and support local ProServe delivery teams as a Subject Matter Expert to deliver transformational ProServe AI/ML engagements for AWS customers.
  3. Pre-sales support – Create and deliver presentations to customers that inspire the art of the possible with AI/ML running at scale in the Cloud. Understand customer requirements and collaborate with AWS sales leaders to scope, present, and win new customer engagements.
  4. Domain Leadership – Identify common customer interest in APJ and innovate new technology offerings. Share real world implementations and recommend new capabilities that would simplify adoption and drive greater value from use of AWS cloud services.
  5. Expertise Transfer – Upskill AWS ProServe builders in APJ on proven ProServe offerings.


BASIC QUALIFICATIONS

  1. 10+ years of consulting experience working with Data and AI/ML solutions.
  2. 10+ years of experience in developing long-term strategies around product/solution roadmap with execution programs to deliver on envisioned strategy.
  3. Recent and demonstrable hands-on experience with AI/ML workloads.
  4. Ability to create compelling customer proposals and executive-level presentation skills.
  5. Expert level understanding of Cloud Computing, Hybrid, Multicloud environments.

PREFERRED QUALIFICATIONS

  1. Experience with pre-sales a plus.
  2. Industry expertise in FSI or Telco is a plus.
  3. AWS Cloud Certifications.
  4. Experience with AWS services.


Posted:January 9, 2025 (Updated about 15 hours ago)

Posted:January 7, 2025 (Updated 2 days ago)

Posted:January 7, 2025 (Updated 2 days ago)

Posted:January 6, 2025 (Updated 3 days ago)

Posted:January 6, 2025 (Updated 4 days ago)

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

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.