Portfolio Lead, Sustainability

DeepMind
London
3 months ago
Applications closed

Related Jobs

View all jobs

Lead Mobile Engineer

Chief Information Security Officer – Managing Director

Automation Engineering GSK Graduate Programme, UK, 2025

UNPAID VOLUNTEER - Chief Technology Officer (CTO) /Deputy CTO

Energy Networks - Senior/ Principal Consultant (Basé à London)

Senior Lead Software Engineer - Python / Credit Technology Data

At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.


Snapshot

The Google DeepMind Impact Accelerator (GDI) has a unique role in Google DeepMind (GDM), to drive real world impact with solutions and resources built on GDM's technologies and expertise that extend the benefits to humanity.


About us

Artificial Intelligence could be one of humanity's most useful inventions. At Google DeepMind, we're a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.


The role

Working in partnership with GDI's leadership, you will develop and be responsible for a portfolio within our AI for Sustainability effort, including directing, organising and driving activities that advance the positive impact to sustainability in this domain area. This is an evolving and dynamic area of Google DeepMind with a collaborative, diverse group that partners closely with a wide variety of teams across Google DeepMind, Alphabet and a range of external partners.


Key responsibilities

  • Identify opportunities to use Google DeepMind technology to solve real-world problems in this domain, and determine the best approach and execution plans for prioritised ideas, alongside research, engineering and GDI teams.
  • Bring together and motivate individuals (including Scientists and Engineers) from across Google DeepMind to work on projects related to AI applications to sustainability.
  • Drive a portfolio of projects related to these applications, taking ownership of defining objectives, outlining strategies, and achieving results.
  • Scope, prototype and launch solutions incorporating research improvements, ideas from stakeholders and the deep understanding of user needs and preferences you have developed, to ensure equal access and wide adoption of the solutions.
  • Build and manage external ecosystem relationships in the specific domain.
  • Deliver continuous success of programs against their objectives, evaluating them structurally and driving interventions when needed.
  • Oversee budgets and resourcing, working closely with the team and program manager to optimise and manage it.

The role will suit candidates who enjoy applying state-of-the-art AI to important real-world problems that maximise positive impact for the wider community.


About you

In order to set you up for success as the Sustainability Portfolio Lead at Google DeepMind, we look for the following skills and experience:

  • Demonstrable experience and knowledge of driving sizeable programs relating to real world AI applications, from inception to delivery in a fast paced and dynamic environment successfully collaborating across multiple high performing stakeholders.
  • Prior professional experience and/or an academic background in an area of sustainability, such as climate, biodiversity or material sciences.
  • Confidence and effectiveness in engaging researchers and engineers. While not an ML specialist yourself, you are able to understand the considerations related to AI research and technologies.
  • Program and Product Management experience; crafting strategic product roadmaps from conception to launch, driving decisions based on insights driving equitable usage.
  • High quality and ethical standard that is showcased on your approach on making decisions and communicating results.
  • Management experience and a proven ability to collaborate with a variety of talented colleagues, teams and partners.
  • Outstanding communication skills and ability to work with both tech and non-tech teams and senior leadership.
  • A passion for Google DeepMind's mission and knowledgeable and excited about AI and its potential for scientific and real-world impact.

Deadline to apply: 5pm GMT, Sunday 5th January.

Note: In the event your application is successful and an offer of employment is made to you, any offer of employment will be conditional on the results of a background check, performed by a third party acting on our behalf. For more information on how we handle your data, please see our Applicant and Candidate Privacy Policy.

#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.

Contract vs Permanent Machine Learning Jobs: Which Pays Better in 2025?

Machine learning (ML) has swiftly become one of the most transformative forces in the UK technology landscape. From conversational AI and autonomous vehicles to fraud detection and personalised recommendations, ML algorithms are reshaping how organisations operate and how consumers experience products and services. In response, job opportunities in machine learning—including roles in data science, MLOps, natural language processing (NLP), computer vision, and more—have risen dramatically. Yet, as the demand for ML expertise booms, professionals face a pivotal choice about how they want to work. Some choose day‑rate contracting, leveraging short-term projects for potentially higher immediate pay. Others embrace fixed-term contract (FTC) roles for mid-range stability, or permanent positions for comprehensive benefits and a well-defined career path. In this article, we will explore these different employment models, highlighting the pros and cons of each, offering sample take‑home pay scenarios, and providing insights into which path might pay better in 2025. Whether you’re a new graduate with a machine learning degree or an experienced practitioner pivoting into an ML-heavy role, understanding these options is key to making informed career decisions.

Machine‑Learning Jobs for Non‑Technical Professionals: Where Do You Fit In?

The Model Needs More Than Math When ChatGPT went viral and London start‑ups raised seed rounds around “foundation models,” many professionals asked, “Do I need to learn PyTorch to work in machine learning?” The answer is no. According to the Turing Institute’s UK ML Industry Survey 2024, 39 % of advertised ML roles focus on strategy, compliance, product or operations rather than writing code. As models move from proof‑of‑concept to production, demand surges for specialists who translate algorithms into business value, manage risk and drive adoption. This guide reveals the fastest‑growing non‑coding ML roles, the transferable skills you may already have, real transition stories and a 90‑day action plan—no gradient descent necessary.

Quantexa Machine‑Learning Jobs in 2025: Your Complete UK Guide to Joining the Decision‑Intelligence Revolution

Money‑laundering rings, sanctioned entities, synthetic identities—complex risks hide in plain sight inside data. Quantexa, a London‑born scale‑up now valued at US $2.2 bn (Series F, August 2024), solves that problem with contextual decision‑intelligence (DI): graph analytics, entity resolution and machine learning stitched into a single platform. Banks, insurers, telecoms and governments from HSBC to HMRC use Quantexa to spot fraud, combat financial crime and optimise customer engagement. With the launch of Quantexa AI Studio in February 2025—bringing generative AI co‑pilots and large‑scale Graph Neural Networks (GNNs) to the platform—the company is hiring at record pace. The Quantexa careers portal lists 450+ open roles worldwide, over 220 in the UK across data science, software engineering, ML Ops and client delivery. Whether you are a graduate data scientist fluent in Python, a Scala veteran who loves Spark or a solutions architect who can turn messy data into knowledge graphs, this guide explains how to land a Quantexa machine‑learning job in 2025.