Planet A Ventures
Location London Address London, England Employment Type Full time Location Type Hybrid Department Engineering Our Mission At Carbon Re, we're on a mission to cut gigatonnes of carbon emissions from the world's biggest emitting industries, like cement, steel, and glass, by applying cutting edge AI where it matters most. We're a small and growing team of scientists, engineers, and strategic thinkers who care deeply about impact and believe in getting there with good humour and urgency. Our SaaS products help heavy industry optimise operations in real time, cutting costs and carbon today while building the foundation for the next industrial revolution. We're looking for a Senior Software Engineer to join our platform team and help us push the boundaries of what AI can do for the planet. We don't draw a specific line between engineering and research teams. We operate as one cohesive unit, sharing tech stack, knowledge, and objectives. Our focus spans from fundamental ML research to commercial grade software development, offering diverse learning and impact opportunities. Why this role exists Carbon Re is scaling deployments from a handful of sites to dozens of plants per year. Large industrial operators have the biggest decarbonisation potential, but they also have strict security and networking constraints. Until recently, most of our systems lived in our own cloud. Now, we're building the capability to run our workloads effectively in our customers' own environments. We need a Software Engineer with solid cloud architecture experience to help us smash this out of the park. You'll be a senior individual contributor partnering closely with product, ML, and solutions teams. Your main responsibilities Own key platform components across AWS and GCP, shaping architecture for scalable, secure systems. Deploy and operate our workloads inside customer owned cloud accounts, working directly with their IT and infrastructure teams to navigate requirements and constraints. Assist more junior team members with their development, helping them learn core software engineering skills and best practices. Propose and drive improvements to existing systems and pipelines. What a great fit looks like You have deep experience with AWS or GCP (bonus points for both!). You have a solid understanding of cloud networking. You're fluent in Python and Terraform. You have designed or owned CI/CD pipelines for frequent, safe releases. You love collaborating with others and are familiar with agile technical practices, including pair programming, mob programming, and TDD. You balance good engineering practices with pragmatism: you know when "good enough now" beats "perfect later". We're a startup! You are comfortable with ambiguity and enjoy owning a problem from discovery to delivery. Bonus points You've worked in industrial, IoT, or similarly complex environments The ways we like to work We are a collaborative team. We regularly and eagerly pair and work through problems together. We love bouncing ideas off each other! We have regular retrospectives to keep getting better as a team. No blame culture: we support each other when things go wrong and always run post mortems so we never make the same mistake twice. You'll get a badge for causing your first production incident We ship fast. We are proud of our CI/CD pipeline and quality gates, and we review our teammates' work quickly. Our small team regularly deploys over a dozen times a day. Yes, we ship on Fridays. We are hooked on observability: we strive to get visibility over all parts of our system to make incident response as painless as possible and to know what needs to improve. In return for your hard work, we'll give you Equity in the company: When we win, you win. You'll get share options, so you're part of our journey from the inside. Flexible working: We trust you to know how and when you work best and to work that out with your team. 30 days of holiday (plus bank holidays). Rest is productive. Take the time you need to recharge A generous pension scheme. We're planning for the future in more ways than one. Our Operating Principles Go Gig or Go Home: High Bar, All In. What we do matters to humanity, to our customers and to each other. We hold ourselves to an extraordinarily high bar and bring the urgency this mission requires. Concrete Honesty: Be honest. As concrete forms the foundation of our world, genuine honesty and transparency are the bedrock of our culture. Autonomous Ownership: High agency, high ownership. We build systems that take control and make things better. We do the same: see it, own it, drive it. Cement it with Kindness & Fun: Have fun, be kind. We're here to extend Earth's life, but ours is still limited. We want to enjoy the ride. To see these in full, Carbon Re's Operating Principles Notion page.
Location London Address London, England Employment Type Full time Location Type Hybrid Department Engineering Our Mission At Carbon Re, we're on a mission to cut gigatonnes of carbon emissions from the world's biggest emitting industries, like cement, steel, and glass, by applying cutting edge AI where it matters most. We're a small and growing team of scientists, engineers, and strategic thinkers who care deeply about impact and believe in getting there with good humour and urgency. Our SaaS products help heavy industry optimise operations in real time, cutting costs and carbon today while building the foundation for the next industrial revolution. We're looking for a Senior Software Engineer to join our platform team and help us push the boundaries of what AI can do for the planet. We don't draw a specific line between engineering and research teams. We operate as one cohesive unit, sharing tech stack, knowledge, and objectives. Our focus spans from fundamental ML research to commercial grade software development, offering diverse learning and impact opportunities. Why this role exists Carbon Re is scaling deployments from a handful of sites to dozens of plants per year. Large industrial operators have the biggest decarbonisation potential, but they also have strict security and networking constraints. Until recently, most of our systems lived in our own cloud. Now, we're building the capability to run our workloads effectively in our customers' own environments. We need a Software Engineer with solid cloud architecture experience to help us smash this out of the park. You'll be a senior individual contributor partnering closely with product, ML, and solutions teams. Your main responsibilities Own key platform components across AWS and GCP, shaping architecture for scalable, secure systems. Deploy and operate our workloads inside customer owned cloud accounts, working directly with their IT and infrastructure teams to navigate requirements and constraints. Assist more junior team members with their development, helping them learn core software engineering skills and best practices. Propose and drive improvements to existing systems and pipelines. What a great fit looks like You have deep experience with AWS or GCP (bonus points for both!). You have a solid understanding of cloud networking. You're fluent in Python and Terraform. You have designed or owned CI/CD pipelines for frequent, safe releases. You love collaborating with others and are familiar with agile technical practices, including pair programming, mob programming, and TDD. You balance good engineering practices with pragmatism: you know when "good enough now" beats "perfect later". We're a startup! You are comfortable with ambiguity and enjoy owning a problem from discovery to delivery. Bonus points You've worked in industrial, IoT, or similarly complex environments The ways we like to work We are a collaborative team. We regularly and eagerly pair and work through problems together. We love bouncing ideas off each other! We have regular retrospectives to keep getting better as a team. No blame culture: we support each other when things go wrong and always run post mortems so we never make the same mistake twice. You'll get a badge for causing your first production incident We ship fast. We are proud of our CI/CD pipeline and quality gates, and we review our teammates' work quickly. Our small team regularly deploys over a dozen times a day. Yes, we ship on Fridays. We are hooked on observability: we strive to get visibility over all parts of our system to make incident response as painless as possible and to know what needs to improve. In return for your hard work, we'll give you Equity in the company: When we win, you win. You'll get share options, so you're part of our journey from the inside. Flexible working: We trust you to know how and when you work best and to work that out with your team. 30 days of holiday (plus bank holidays). Rest is productive. Take the time you need to recharge A generous pension scheme. We're planning for the future in more ways than one. Our Operating Principles Go Gig or Go Home: High Bar, All In. What we do matters to humanity, to our customers and to each other. We hold ourselves to an extraordinarily high bar and bring the urgency this mission requires. Concrete Honesty: Be honest. As concrete forms the foundation of our world, genuine honesty and transparency are the bedrock of our culture. Autonomous Ownership: High agency, high ownership. We build systems that take control and make things better. We do the same: see it, own it, drive it. Cement it with Kindness & Fun: Have fun, be kind. We're here to extend Earth's life, but ours is still limited. We want to enjoy the ride. To see these in full, Carbon Re's Operating Principles Notion page.
Planet A Ventures
Location London Address London, England Employment Type Full time Location Type Hybrid Department Machine Learning Our Mission At Carbon Re We're on a mission to cut gigatonnes of carbon emissions from the world's biggest emitting industries, like cement, steel, and glass, by applying cutting edge AI where it matters most. We're a small and growing team of scientists, engineers, and strategic thinkers who care deeply about impact and believe in getting there with good humour and urgency. Our SaaS products help heavy industry optimise operations in real time, cutting costs and carbon today while building the foundation for the next industrial revolution. We are seeking a Senior Machine Learning Engineer to help build the models that underpin these control systems and help us level up our machine learning infrastructure. We don't draw a specific line between engineering and research teams. We operate as one cohesive unit, sharing tech stack, knowledge, and objectives. Our focus spans from fundamental ML research to commercial grade software development, offering diverse learning and impact opportunities. Your main responsibilities Work in the machine learning team as an individual contributor, building, testing and deploying our models. Contribute to technical innovation and problem solving across the machine learning lifecycle. Collaborate with the product team on customer projects, planning, designing and delivering the work packages required, as well as playing a significant role in the development of our wider product. Help establish best practices to improve our internal processes. Contribute to the design and implementation of robust, maintainable and scalable machine learning systems. You will also contribute to our fear free development process by building tooling that helps the team move faster and more sustainably. You will be supported by continuous builds, tests, a constructive review system, and a strong culture of improving engineering processes. What a great fit looks like You have 2 or more years of experience as a machine learning engineer. You are familiar with several ML techniques, and have both theoretical ML knowledge and experience implementing different types of solutions. You are proficient in Python and have a good understanding of the ecosystem of tools and libraries that support ML development (e.g., scikit learn, PyTorch). You have experience working in a scientific environment across disciplines (particularly physics, chemistry, materials science, and engineering), either through previous roles or study. Are passionate about making a positive impact on climate change mitigation and possess a strong interest in our mission. You'll excel if You have prior experience with time series modelling and industrial or IoT data. You have experience in any of: dynamical systems, reinforcement learning, system identification, optimisation or Bayesian statistics. You are used to working in a fast paced startup environment with an agile process. You have a degree in machine learning, physics or chemistry. You are hungry for responsibility, enthusiastic about taking on the design and development of solutions to difficult problems, and eager to drive the progress of new products. You have a solid understanding of modern cloud compute infrastructure as it relates to machine learning, and experience in working with AWS, GCP, Azure, or other vendors. The interview process We run a multiple part interview process. You can choose to interview remotely or on site for some of the interviews, but it's easier to build rapport in person. Intro call - meeting with our talent partner Fundamentals of Machine Learning - a discussion with members of the machine learning team around some of the fundamentals of ML and your understanding and application of them. (1 hour, remote) Technical interview - (half day, in person/remote) Problem solving - applying machine learning, scientific understanding and problem solving to some of the challenges we tackle day to day in the ML team. Engineering - a practical exercise focused on software engineering for ML. Architecture - a discussion based exercise around systems design for ML. Behaviours and Operating Principles - a meeting with two members of our team to discuss your past experiences, to understand how you would fit in with our operating principles. (1 hour, remote) Meet the exec - an informal chat to meet either Josh (CEO) or Buffy (COO) (30 minutes, in person/remote) In the same way we reference check our candidates before making final offers, we invite you to reference check us by chatting informally with any team members you didn't meet during the hiring process. Once the interviews are over, we'll try to make a decision as quickly as possible, and you can ask us for feedback at any stage. In return for your hard work, we'll give you Equity in the company: When we win, you win. You'll get share options, so you're part of our journey from the inside. Flexible working: We trust you to know how and when you work best and to work that out with your team. 30 days of holiday (plus bank holidays). Rest is productive. Take the time you need to recharge. A generous pension scheme: We're planning for the future in more ways than one. Our Operating Principles Go Gig or Go Home: High Bar, All In. What we do matters to humanity, to our customers and to each other. We hold ourselves to an extraordinarily high bar and bring the urgency this mission requires. Concrete Honesty: Be honest. As concrete forms the foundation of our world, genuine honesty and transparency are the bedrock of our culture. Autonomous Ownership: High agency, high ownership. We build systems that take control and make things better. We do the same: see it, own it, drive it. Cement it with Kindness & Fun: Have fun, be kind. We're here to extend Earth's life, but ours is still limited. We want to enjoy the ride.
Location London Address London, England Employment Type Full time Location Type Hybrid Department Machine Learning Our Mission At Carbon Re We're on a mission to cut gigatonnes of carbon emissions from the world's biggest emitting industries, like cement, steel, and glass, by applying cutting edge AI where it matters most. We're a small and growing team of scientists, engineers, and strategic thinkers who care deeply about impact and believe in getting there with good humour and urgency. Our SaaS products help heavy industry optimise operations in real time, cutting costs and carbon today while building the foundation for the next industrial revolution. We are seeking a Senior Machine Learning Engineer to help build the models that underpin these control systems and help us level up our machine learning infrastructure. We don't draw a specific line between engineering and research teams. We operate as one cohesive unit, sharing tech stack, knowledge, and objectives. Our focus spans from fundamental ML research to commercial grade software development, offering diverse learning and impact opportunities. Your main responsibilities Work in the machine learning team as an individual contributor, building, testing and deploying our models. Contribute to technical innovation and problem solving across the machine learning lifecycle. Collaborate with the product team on customer projects, planning, designing and delivering the work packages required, as well as playing a significant role in the development of our wider product. Help establish best practices to improve our internal processes. Contribute to the design and implementation of robust, maintainable and scalable machine learning systems. You will also contribute to our fear free development process by building tooling that helps the team move faster and more sustainably. You will be supported by continuous builds, tests, a constructive review system, and a strong culture of improving engineering processes. What a great fit looks like You have 2 or more years of experience as a machine learning engineer. You are familiar with several ML techniques, and have both theoretical ML knowledge and experience implementing different types of solutions. You are proficient in Python and have a good understanding of the ecosystem of tools and libraries that support ML development (e.g., scikit learn, PyTorch). You have experience working in a scientific environment across disciplines (particularly physics, chemistry, materials science, and engineering), either through previous roles or study. Are passionate about making a positive impact on climate change mitigation and possess a strong interest in our mission. You'll excel if You have prior experience with time series modelling and industrial or IoT data. You have experience in any of: dynamical systems, reinforcement learning, system identification, optimisation or Bayesian statistics. You are used to working in a fast paced startup environment with an agile process. You have a degree in machine learning, physics or chemistry. You are hungry for responsibility, enthusiastic about taking on the design and development of solutions to difficult problems, and eager to drive the progress of new products. You have a solid understanding of modern cloud compute infrastructure as it relates to machine learning, and experience in working with AWS, GCP, Azure, or other vendors. The interview process We run a multiple part interview process. You can choose to interview remotely or on site for some of the interviews, but it's easier to build rapport in person. Intro call - meeting with our talent partner Fundamentals of Machine Learning - a discussion with members of the machine learning team around some of the fundamentals of ML and your understanding and application of them. (1 hour, remote) Technical interview - (half day, in person/remote) Problem solving - applying machine learning, scientific understanding and problem solving to some of the challenges we tackle day to day in the ML team. Engineering - a practical exercise focused on software engineering for ML. Architecture - a discussion based exercise around systems design for ML. Behaviours and Operating Principles - a meeting with two members of our team to discuss your past experiences, to understand how you would fit in with our operating principles. (1 hour, remote) Meet the exec - an informal chat to meet either Josh (CEO) or Buffy (COO) (30 minutes, in person/remote) In the same way we reference check our candidates before making final offers, we invite you to reference check us by chatting informally with any team members you didn't meet during the hiring process. Once the interviews are over, we'll try to make a decision as quickly as possible, and you can ask us for feedback at any stage. In return for your hard work, we'll give you Equity in the company: When we win, you win. You'll get share options, so you're part of our journey from the inside. Flexible working: We trust you to know how and when you work best and to work that out with your team. 30 days of holiday (plus bank holidays). Rest is productive. Take the time you need to recharge. A generous pension scheme: We're planning for the future in more ways than one. Our Operating Principles Go Gig or Go Home: High Bar, All In. What we do matters to humanity, to our customers and to each other. We hold ourselves to an extraordinarily high bar and bring the urgency this mission requires. Concrete Honesty: Be honest. As concrete forms the foundation of our world, genuine honesty and transparency are the bedrock of our culture. Autonomous Ownership: High agency, high ownership. We build systems that take control and make things better. We do the same: see it, own it, drive it. Cement it with Kindness & Fun: Have fun, be kind. We're here to extend Earth's life, but ours is still limited. We want to enjoy the ride.