300 Microsoft Research Cambridge jobs in London

The Ellison Institute of Technology (EIT) Oxford’s purpose is to have a global impact by fundamentally reimagining the way science and technology translate into end-to-end solutions and delivering these solutions in programmes and platforms that respond to humanity’s most challenging problems. 

EIT Oxford will ensure scientific discoveries and pioneering science are turned into products for the benefit of society that can have high-impact worldwide and, over time, be commercialised to ensure long-term sustainability. 

Led by a faculty of world experts, EIT Oxford seeks to solve the world’s most challenging problems across four high-risk, high-reward, high-impact humane endeavours: health and medical science; food security and sustainable agriculture; climate change and clean energy; and government innovation in an era of artificial intelligence. 

EIT Oxford is investing significant resources in a new world-class research and development facility in the Oxford Science Park. Set for completion in 2027, the state-of-the-art campus includes 300,000 sq ft of research laboratories, an oncology and preventative care clinic, and educational and meeting spaces. Together, they create the perfect environment for EIT Oxford experts to take ground-breaking ideas from research to broad implementation. The new facility will further EIT’s current partnership with the University of Oxford and become the new home for Ellison Scholars. 

EIT Oxford is committed to cultivating a community where excellence is achieved through collaboration, trust, innovation and tenacity. We foster an environment where everyone’s experience and expertise are valued. We are curious and resilient in our efforts to drive long-term, sustainable innovation to meet humanity’s most enduring challenges. 

 
Job summary 
We are looking for Research Engineers who will work with large scale   datasets from different modalities, including biomolecular data, such as proteins and DNA, 2D and 3D images or graph-structured data. You will design and implement advanced ML architectures and workflows encompassing multimodal generative models and physics-based modelling. 

Responsibilities 

• Design and implement advanced ML architectures 

• Develop robust model evaluation pipelines. 

• Optimize model architectures for performance and reliability. 

• Drive best practices in code quality, reproducibility, and collaboration. 

• Build and maintain large-scale ML systems that process biomolecule datasets. 

• Work with domain specialists to incorporate wet lab data and HPC simulations. 

• Help to build and maintain large-scale generative models of molecular data. 

Requirements

Qualifications 

• Advanced degree in Computer Science, Physics, Chemistry, or Materials Science with a strong ML focus. 

• Hands-on experience in GPU-based computing, HPC integrations, and distributed system architectures. 

• Proficiency with deep learning frameworks (e.g. PyTorch) and scientific software (e.g., molecular simulation). 

• Strong understanding of data modeling and pipeline optimization for large-scale experiments. 

• Ability to collaborate effectively with multidisciplinary teams and communicate complex concepts clearly. 

Team:  Machine Learning

Location:  London (On-site; Liverpool Street)

Employment Type:  Full-time and Permanent

Remuneration:  £90 - 120k  Base Salary + Discretionary Bonus + Equity

We are a stealth-mode AI laboratory researching and developing Machine Learning models.

The founding team consists of Cambridge graduates and former engineers at Google, Meta, Bloomberg, Microsoft and Amazon. We are backed by prominent investors from the US and the UK, including institutional VC funds and C-level executives of global technology companies.

In this role, you will:

• Design, develop and train large multimodal machine learning models across all stages: pre-training, post-training, evaluations and inference.
• Work closely with clients to understand data and model architecture requirements for their business needs.
• Be given a high degree of autonomy and ownership over your work.
• Co-hire your future colleagues.
• Work closely with the founding team and contribute towards best practices, standards, and culture of the company.

What we are looking for:

• Research engineering:  2-3 years of industry experience in complex machine learning projects including data processing and training models in a distributed environment.
• LLMs:  Strong understanding of LLM architectures, pre and/or post-training, evaluations and inference.
• Programming languages:  Excellent proficiency in Python using PyTorch/TensorFlow/JAX framework.
• Customer facing:  Experience working directly with customers to solve applied problems, including product integration.
• Cloud-native technologies:  Experience in developing and deploying in cloud platforms (e.g., AWS, GCP or Azure), an understanding of containerisation (e.g., Docker).
• Algorithms and data structures:  Excellent understanding of core CS fundamentals, including common abstract data structures and algorithms with the ability to apply them to optimise production systems.
• Problem solving:  Strong analytical problem-solving skills and attention to detail. You have the ability to break down complex problems into actionable tasks.
• Collaboration and communication:  Excellent interpersonal and communication skills with a desire to learn.

We would like to acknowledge that almost no candidate checks every box – and that is perfectly fine. If you are passionate about data and enjoy solving complex challenges, we would love to hear from you.

Nice to have:

• Publications:  At top-tier ML/CV/NLP conferences (NeurIPS, ICML, ICLR, CVPR, ICCV)
• Open-source:  Contributions to and experience in open-source projects.
• Startup experience:  Experience with a startup work environment and wider ecosystem.

Why join us?

• Work in an environment conducting cutting-edge research in AI.
• An official role title of “Founding Research Engineer” - make an impact on day one.
• Competitive salary, equity and benefits package.
• 28 days + public holidays allowance.
• Opportunities for professional growth and progression with your career.
• Work on challenging engineering problems that have a real impact on the industry.
• Work with high-profile customers and technology partners.

Welcome to the video first world

From your everyday PowerPoint presentations to Hollywood movies, AI will transform the way we create and consume content.

Today, people want to watch and listen, not read — both at home and at work. If you’re reading this and nodding, check out our brand video .

Despite the clear preference for video, communication and knowledge sharing in the business environment are still dominated by text, largely because high-quality video production remains complex and challenging to scale—until now….

Meet Synthesia

We're on a mission to make video easy for everyone. Born in an AI lab, our AI video communications platform simplifies the entire video production process, making it easy for everyone, regardless of skill level, to create, collaborate, and share high-quality videos. Whether it's for delivering essential training to employees and customers or marketing products and services, Synthesia enables large organizations to communicate and share knowledge through video quickly and efficiently. We’re trusted by leading brands such as Heineken, Zoom, Xerox, McDonald’s and more. Read stories from happy customers and what 1,200+ people say on G2 .

In February 2024, G2 named us as the fastest growing company in the world. Today, we're at a $2.1bn valuation and we recently raised our Series D. This brings our total funding to over $330M from top-tier investors, including Accel, Nvidia, Kleiner Perkins, Google and top founders and operators including Stripe, Datadog, Miro, Webflow, and Facebook.

What you'll do at Synthesia:

As a Research Engineer you will join a team of 40+ Researchers and Engineers within the R&D Department working on cutting edge challenges in the Generative AI space, with a focus on creating highly realistic, emotional and life-like Synthetic humans through text-to-video. Within the team you’ll have the opportunity to work on the applied side of our research efforts and directly impact our solutions that are used worldwide by over 55,000 businesses. If you are an expert in post-training Diffusion models for generative AI, this is your chance. This is an opportunity to work for a company that is impacting businesses at a rapid pace across the globe.

In this position, you’ll join our Post-Training Team that works on generative video creation. You will make it possible to apply our foundational models to production use cases. This includes projects such as:

• Apply DPO (direct preference optimisation) to pre-trained models.
• Adapt models to extend their capabilities, for instance, by changing conditioning inputs.
• Build solutions for dubbing and evaluate the quality of lip-sync.
• Implement post-training optimization techniques, such as quantization, pruning and distillation, to improve the efficiency of diffusion models used in avatar generation.
• Analyze and address challenges related to model performance, ensuring high-quality output in avatar rendering.
• Stay updated with the latest research and advancements in diffusion models, adversarial networks and post-training optimization methods.

What we're looking for:

• You have a background in Computer Vision / Computer Science and 3+ years of industry experience.
• You have knowledge of recent advancements in post-training techniques. (for instance distillation, adversarial networks and efficient attention)
• You have worked with generative models for images and/or videos (Diffusion/GAN) preferably in the avatar domain.
• You are interested in doing research, trying new things and pushing the boundaries, going beyond what’s already known.
• You have experience in using most modern frameworks for machine learning and deep learning.
• You have great coding skills in Python and you care about writing clean code.
• You have experience with SDLC tools (Git), preferably CI/CD

Why join us?

We’re living the golden age of AI. The next decade will yield the next iconic companies, and we dare to say we have what it takes to become one. Here’s why,

Our culture

At Synthesia we’re passionate about building, not talking, planning or politicising. We strive to hire the smartest, kindest and most unrelenting people and let them do their best work without distractions. Our work principles serve as our charter for how we make decisions, give feedback and structure our work to empower everyone to go as fast as possible. You can find out more about these principles here.

Serving 50,000+ customers (and 50% of the Fortune 500)

We’re trusted by leading brands such as Heineken, Zoom, Xerox, McDonald’s and more. Read stories from happy customers and what 1,200+ people say on G2 .

Proprietary AI technology

Since 2017, we’ve been pioneering advancements in Generative AI. Our AI technology is built in-house, by a team of world-class AI researchers and engineers. Learn more about our AI Research Lab and the team behind.

AI Safety, Ethics and Security

AI safety, ethics, and security are fundamental to our mission. While the full scope of Artificial Intelligence's impact on our society is still unfolding, our position is clear: People first. Always. Learn more about our commitments to AI Ethics, Safety & Security .

The good stuff.

• Competitive compensation (salary + stock options + bonus)
• Hybrid work setting with an office in London, Amsterdam, Zurich, Munich, or remote in Europe.
• 25 days of annual leave + public holidays
• Great company culture with the option to join regular planning and socials at our hubs
• + other benefits depending on your location

You can see more about Who we are and How we work here:

At Plumerai, we make it easy and affordable for developers to add highly accurate AI to their embedded devices and thereby enable them to create amazing new products. We combine our on-device Tiny AI software with our cloud-based multimodal LLMs, providing People Detection, Video Search, Familiar Face Identification, AI Captions and more.

Major enterprises deploy our advanced computer vision models on millions of smart home cameras in the field and we’re rapidly expanding into commercial security, retail, assisted living, and more. The best solution runs as much as possible on-device to enable low-power, accurate, and private AI products. This is where Plumerai leads, demonstrating better accuracy even than Google Nest. We are now starting to invest heavily in market adoption.

We build the most accurate and efficient AI solutions by vertically integrating all layers of the stack. From data collection and curation, custom training software, model architectures, multimodal LLMs, pre- and postprocessing, and all the way down to the fastest inference engines. Not only does our team have a deep theoretical understanding about all these components, we also know how to ship fast and often.

Our team is based in London and Amsterdam, we have recently raised funding to provide multiple years of runway, while our recurring revenue is growing rapidly. We are backed by world-class investors such as Tony Fadell (creator of iPod, iPhone; founder of Nest), Hermann Hauser (founder of Arm), Zoubin Ghahramani (Google DeepMind), and others.
Learn more here:
TechCrunch: Tony Fadell-backed Plumerai brings on-device AI to home security cameras
Plumerai raises $8.7M Series A to connect Vision LLMs to trillions of edge devices.

Role description

We are looking for an AI Research Engineer that can help us develop state of the art AI products. This can involve anything from improving our training algorithms, training and integrating multimodal LLMs, building our data pipeline, designing new model architectures to using tried and tested ML approaches and coming up with clever algorithms. You will help us build new AI features that will be shipped to millions of camera devices in the field. Together we are building the most advanced AI for embedded devices.

What you will be doing

• We combine our Tiny AI with multimodal LLMs to enable our advanced AI features for our customers. You will use and improve multimodal LLMs to achieve new functionality for our customers and optimize their deployments (cloud and edge).
• Some of our deep learning models are truly tiny - the memory footprint of our smallest computer vision model is just 1MB. You will train and design more accurate models, while also enabling new and more complex AI applications on low-cost and low-power hardware.
• You will improve our data pipeline, model architectures and training software. Sometimes there is relevant literature available, but novel approaches and clever hacks are often required for the problems that we are working on.
• You will use our Kubernetes cluster to deploy PyTorch and TensorFlow training jobs, Snowflake and Dataflow to build datasets, tools like Streamlit to prototype new demos (try one of our live demos here ) and lots of GPUs on GCP for training new models and auto-labeling data.

Requirements

What You Need

• Very strong software engineering skills and proficiency in Python.
• Comfortable with frameworks such as PyTorch, TensorFlow, Keras, or JAX.
• Strong experience with computer vision and multimodal LLMs.
• Experience working in a team on the same software project.

Nice To Have

• Trained neural networks that moved into production.
• Industry experience with efficient inference deployments (cloud or edge).
• Experience with Deep Reinforcement Learning.

Benefits

What we offer

• Competitive salary.
• Generous equity stake in the company.
• Relocation assistance.
• Choose your own laptop.
• 25 days of paid vacation time in addition to bank holidays.
• Ability to attend top research conferences like NeurIPS, ICML and CVPR.

We only consider applicants who are currently based in, or willing to relocate to, London or Amsterdam. We have flexible working hours and work together from our offices on at least 2 fixed days per week.

At Plumerai, we make it easy and affordable for developers to add highly accurate AI to their embedded devices and thereby enable them to create amazing new products. We combine our on-device Tiny AI software with our cloud-based multimodal LLMs, providing People Detection, Video Search, Familiar Face Identification, AI Captions and more.

Major enterprises deploy our advanced computer vision models on millions of smart home cameras in the field and we’re rapidly expanding into commercial security, retail, assisted living, and more. The best solution runs as much as possible on-device to enable low-power, accurate, and private AI products. This is where Plumerai leads, demonstrating better accuracy even than Google Nest. We are now starting to invest heavily in market adoption.

We build the most accurate and efficient AI solutions by vertically integrating all layers of the stack. From data collection and curation, custom training software, model architectures, multimodal LLMs, pre- and postprocessing, and all the way down to the fastest inference engines. Not only does our team have a deep theoretical understanding about all these components, we also know how to ship fast and often.

Our team is based in London and Amsterdam, we have recently raised funding to provide multiple years of runway, while our recurring revenue is growing rapidly. We are backed by world-class investors such as Tony Fadell (creator of iPod, iPhone; founder of Nest), Hermann Hauser (founder of Arm), Zoubin Ghahramani (Google DeepMind), and others.
Learn more here:
TechCrunch: Tony Fadell-backed Plumerai brings on-device AI to home security cameras
Plumerai raises $8.7M Series A to connect Vision LLMs to trillions of edge devices.

We are looking for an AI Research Engineer that can help us develop state of the art AI products. This can involve anything from improving our training algorithms, training and integrating multimodal LLMs, building our data pipeline, designing new model architectures to using tried and tested ML approaches and coming up with clever algorithms. You will help us build new AI features that will be shipped to millions of camera devices in the field. Together we are building the most advanced AI for embedded devices.

What you will be doing

• We combine our Tiny AI with multimodal LLMs to enable our advanced AI features for our customers. You will use and improve multimodal LLMs to achieve new functionality for our customers and optimize their deployments (cloud and edge).
• Some of our deep learning models are truly tiny - the memory footprint of our smallest computer vision model is just 1MB. You will train and design more accurate models, while also enabling new and more complex AI applications on low-cost and low-power hardware.
• You will improve our data pipeline, model architectures and training software. Sometimes there is relevant literature available, but novel approaches and clever hacks are often required for the problems that we are working on.
• You will use our Kubernetes cluster to deploy PyTorch and TensorFlow training jobs, Snowflake and Dataflow to build datasets, tools like Streamlit to prototype new demos (try one of our live demos here ) and lots of GPUs on GCP for training new models and auto-labeling data.

Requirements

What You Need

• Very strong software engineering skills and proficiency in Python.

• Comfortable with frameworks such as PyTorch, TensorFlow, Keras, or JAX.
• Strong experience with computer vision and multimodal LLMs.
• Experience working in a team on the same software project.

Nice To Have

• Trained neural networks that moved into production.
• Industry experience with efficient inference deployments (cloud or edge).
• Experience with Deep Reinforcement Learning.

Benefits

What we offer

• Competitive salary.
• Generous equity stake in the company.
• Relocation assistance.
• Choose your own laptop.
• 25 days of paid vacation time in addition to bank holidays.
• Ability to attend top research conferences like NeurIPS, ICML and CVPR.

We only consider applicants who are currently based in, or willing to relocate to, London or Amsterdam. We have flexible working hours and work together from our offices on at least 2 fixed days per week.

About Arondite

Arondite is building the next generation of autonomous systems, software and AI to solve the world's most important frontier problems across defence, critical industries and the humanitarian sector. We are looking for mission-driven engineers who want to be part of a highly motivated team and build things that make a positive difference.

The Role

Arondite is looking for talented and flexible AI engineers to work on machine learning models for a range of autonomous systems, operating in the air, on the land and under the sea.

You will be developing models using open-source tools such as OpenCV and PyTorch for inclusion within fully integrated hardware/software products. You will be building algorithms to aid in areas such as navigation, image processing, sensor data processing and sensor fusion.

As a member of a company building integrated products, you will be able to influence the design and implementation of the data collection mechanisms, leading to more efficient models and faster training. You will also work closely with end users to rapidly understand and improve real-world model performance.

As an early hire within a start-up, you will have the opportunity to set up and drive AI development within the company. You will potentially lead the function and build a broader team as we continue to expand and build more diverse products. Regardless of previous experience, you will review the output of other engineers to check their work and provide feedback - everyone’s input is valued.

Requirements

You should apply if you have:

• BSc/BEng or MSc/MEng in AI, Computer Science, Data Science, Engineering or a related technical subject
• Strong programming skills in Python, as well as C++, Java or Rust
• Practical experience in developing machine learning models for sensor data processing
• Keen interest in applying cutting-edge machine learning approaches to real-world problems
• Interest in optimising data collection to improve machine learning performance
• Good understanding of resource optimisation of AI models to run on discrete / edge platforms

Note: The above describes the perfect candidate. We encourage you to apply even if you only partially fulfil this list.

Nice to have:

• Knowledge of MLOps in enabling machine learning to be deployed and maintained in end-user products
• Image and data processing for noise reduction / filtering
• Experience in visual representation of complex sensor data

All engineers at Arondite are expected to:

• Communicate effectively within a multi-disciplinary team of hardware, software and AI engineers
• Be resourceful and open-minded in seeking solutions to engineering challenges
• Teach themselves to be the expert, if we don’t already have one in a particular area

Please note: This is an in-person position based in London. The successful candidate must by the start of their employment have permission to work in the UK.

Benefits

We offer:

• The opportunity to work with world-class engineers on a wide range of technologies
• Free training and education to quickly fill knowledge gaps
• The best resources and equipment required to do your job
• Exposure to working closely with customers on real problems
• Free meals and snacks in the office
• 7% employer pension contribution
• Employee Stock Options for everyone, so we all have a stake in the company’s growth
• Relocation support

Team:  Machine Learning

Location:  London (On-site; Liverpool Street)

Employment Type:  Full-time and Permanent

Remuneration:  £70 - 90k  Base Salary + Discretionary Bonus + Equity

We are a stealth-mode AI laboratory researching and developing Machine Learning models.

The founding team consists of Cambridge graduates and former engineers at Google, Meta, Bloomberg, Microsoft and Amazon. We are backed by prominent investors from the US and the UK, including institutional VC funds and C-level executives of global technology companies.

In this role, you will:

• Design, develop and train large multimodal machine learning models across all stages: pre-training, post-training, evaluations and inference.
• Work closely with clients to understand data and model architecture requirements for their business needs.
• Be given a high degree of autonomy and ownership over your work.
• Co-hire your future colleagues.
• Work closely with the founding team and contribute towards best practices, standards, and culture of the company.

What we are looking for:

• Research engineering:  Industry experience in complex machine learning projects including data processing and training models in a distributed environment.
• LLMs:  Understanding of LLM architectures, pre and/or post-training, evaluations and inference.
• Programming languages:  Proficiency in Python using PyTorch/TensorFlow/JAX framework.
• Cloud-native technologies:  Experience in developing and deploying in cloud platforms (e.g., AWS, GCP or Azure), an understanding of containerisation (e.g., Docker).
• Algorithms and data structures:  Excellent understanding of core CS fundamentals, including common abstract data structures and algorithms with the ability to apply them to optimise production systems.
• Problem solving:  Strong analytical problem-solving skills and attention to detail. You have the ability to break down complex problems into actionable tasks.
• Collaboration and communication:  Excellent interpersonal and communication skills with a desire to learn.

We would like to acknowledge that almost no candidate checks every box – and that is perfectly fine. If you are passionate about data and enjoy solving complex challenges, we would love to hear from you.

Nice to have:

• Publications:  At top-tier ML/CV/NLP conferences (NeurIPS, ICML, ICLR, CVPR, ICCV)
• Open-source:  Contributions to and experience in open-source projects.
• Startup experience:  Experience with a startup work environment and wider ecosystem.

Why join us?

• Work in an environment conducting cutting-edge research in AI.
• An official role title of “Founding Research Engineer” - make an impact on day one.
• Competitive salary, equity and benefits package.
• 28 days + public holidays allowance.
• Opportunities for professional growth and progression with your career.
• Work on challenging engineering problems that have a real impact on the industry.
• Work with high-profile customers and technology partners.

Team:  Machine Learning

Location:  London (On-site; Liverpool Street)

Employment Type:  Full-time and Permanent

Remuneration:  £120 - 160k Base Salary + Discretionary Bonus + Equity

We are a stealth-mode AI laboratory researching and developing Machine Learning models.

The founding team consists of Cambridge graduates and former engineers at Google, Meta, Bloomberg, Microsoft and Amazon. We are backed by prominent investors from the US and the UK, including institutional VC funds and C-level executives of global technology companies.

In this role, you will:

• Design, develop and train large multimodal machine learning models across all stages: pre-training, post-training, evaluations and inference.
• Work closely with clients to understand data and model architecture requirements for their business needs.
• Be given a high degree of autonomy and ownership over your work.
• Co-hire your future colleagues.
• Work closely with the founding team and contribute towards best practices, standards, and culture of the company.

What we are looking for:

• Research engineering:  5+ years of industry experience in complex machine learning projects including data processing and training models in a distributed environment.
• LLMs:  Deep understanding of LLM architectures, pre and/or post-training, evaluations and inference.
• Programming languages:  Excellent proficiency in Python using PyTorch/TensorFlow/JAX framework.
• Customer facing:  Experience working directly with customers to solve applied problems, including product integration.
• Cloud-native technologies:  Experience in developing and deploying in cloud platforms (e.g., AWS, GCP or Azure), an understanding of containerisation (e.g., Docker).
• Algorithms and data structures:  Excellent understanding of core CS fundamentals, including common abstract data structures and algorithms with the ability to apply them to optimise production systems.
• Problem solving:  Strong analytical problem-solving skills and attention to detail. You have the ability to break down complex problems into actionable tasks.
• Collaboration and communication:  Excellent interpersonal and communication skills with a desire to learn.

We would like to acknowledge that almost no candidate checks every box – and that is perfectly fine. If you are passionate about data and enjoy solving complex challenges, we would love to hear from you.

Nice to have:

• Publications:  At top-tier ML/CV/NLP conferences (NeurIPS, ICML, ICLR, CVPR, ICCV)
• Open-source:  Contributions to and experience in open-source projects.
• Startup experience:  Experience with a startup work environment and wider ecosystem.

Why join us?

• Work in an environment conducting cutting-edge research in AI.
• An official role title of “Founding Research Engineer” - make an impact on day one.
• Competitive salary, equity and benefits package.
• 28 days + public holidays allowance.
• Opportunities for professional growth and progression with your career.
• Work on challenging engineering problems that have a real impact on the industry.
• Work with high-profile customers and technology partners.

• Lead and mentor a team of AI researchers and engineers.
• Define and execute the AI research strategy and roadmap.
• Design, develop, and implement advanced AI models and algorithms.
• Oversee the entire lifecycle of AI projects, from ideation to deployment.
• Conduct cutting-edge research in areas like ML, DL, NLP, and Computer Vision.
• Ensure the scalability, performance, and efficiency of AI systems.
• Collaborate with product teams to integrate AI solutions into applications.
• Publish research findings and present work at leading conferences.
• Stay abreast of the latest advancements in AI and machine learning.
• Foster a culture of innovation and knowledge sharing within the team.

• Ph.D. or M.S. in Computer Science, Artificial Intelligence, or a related field.
• Significant experience (5+ years) in AI research and development, with proven leadership experience.
• Expertise in machine learning, deep learning, NLP, or computer vision.
• Proficiency in programming languages such as Python and AI frameworks (TensorFlow, PyTorch).
• Strong understanding of algorithm design, data structures, and software engineering principles.
• Proven ability to lead and mentor technical teams.
• Excellent problem-solving, analytical, and critical thinking skills.
• Strong communication and presentation skills.
• Experience with cloud platforms (AWS, Azure, GCP) and MLOps is a plus.