Role Description:

We are looking for an independent, dedicated Senior ML Engineer to join the Visual Computing Group (VCG) and contribute to redefining the world of game play and live streaming via advanced R&D. VCG’s mission is to design and deploy advanced neural networks and machine learning (ML) for game rendering and streaming systems of SIE that exceed the state-of-the-art in runtime efficiency, visual quality and latency.

What you’ll be doing:

• Develop and improve core generative models for graphics and video processing for a variety of applications, such as live video streaming, game rendering, etc.
• Research and prototyping of new methods for graphics or video enhancement, and data generation pipelines from generative models
• Collaborate with team members on drafting publications and patent submissions
• Participate and assist the team in core R&D work with other teams within Sony Interactive Entertainment

What we’re looking for:

• PhD or MSc in Computer Science, Electronic Engineering, Artificial Intelligence, Machine Learning, Computer Graphics or a related field, or equivalent skills evidenced by work experience in the specific domain of the post
• 5+ years of experience in demonstrable research experience in industry or academia.
• Strong background in: TensorFlow or PyTorch; Python and packages/libraries related to computer vision or graphics; evidenced by the development of advanced applications in image/video/graphics processing or computer vision (minimum of 3 years of experience for ML engineer, minimum 5 years for Senior ML engineer),
• Evidence of leading technical developments by at least 1 research publication in a top-tier conference like CVPR, ECCV, ICCV, SIGGRAPH or similar
• Solid background in one or more of the following:

(i) neural network architectures, evidenced (for example) by knowledge of how to formulate and test advanced loss functions in neural network design;

(ii) design and test of advanced convolutional, recurrent, transformer-based, diffusion-based or other neural network architectures in a task-specific manner;

(iii) some experience in training, validation and evaluation of deep neural network models on large datasets, evidenced by experience in using Python libraries like HDF5 or similar

Desired qualifications:

• Publications, e.g. in top-tier conferences and journals: IEEE Transactions on Image Processing, IEEE Transactions on Circuits and Systems for Video Technology, conferences like IEEE CVPR/ICCV/ECCV, NeurIPS, ICML, ICLR, or similar
• Some theoretical understanding of the graphics pipeline, including coordinate transformations between frames of reference, PBR materials, rasterization, lighting, and ray tracing
• Experience in image processing theory and methods, evidenced by the development of practical designs in this area
• Some experience with 3D engines such as Unreal or Unity; in particular, generation of datasets, extraction of G-buffers, motion vectors, etc.

Benefits:

• Discretionary bonus opportunity
• Hybrid Working (within Flexmodes)
• Private Medical Insurance
• Dental Scheme
• 25 days holiday per year
• On Site Gym
• Subsidised Café
• Free soft drinks
• On site bar
• Access to cycle garage and showers

Role Description:

We are looking for an independent, dedicated Machine Learning Engineer/Senior ML Engineer to join the Visual Computing Group (VCG) and contribute to redefining the world of game play and live streaming via advanced R&D. VCG’s mission is to design and deploy advanced neural networks and machine learning (ML) for game rendering and streaming systems of SIE that exceed the state-of-the-art in runtime efficiency, visual quality and latency.

What you’ll be doing:

• Develop and improve core generative models for graphics and video processing for a variety of applications, such as live video streaming, game rendering, etc.
• Research and prototyping of new methods for graphics or video enhancement, and data generation pipelines from generative models
• Collaborate with team members on drafting publications and patent submissions
• Participate and assist the team in core R&D work with other teams within Sony Interactive Entertainment

What we’re looking for:

• PhD or MSc in Computer Science, Electronic Engineering, Artificial Intelligence, Machine Learning, Computer Graphics or a related field, or equivalent skills evidenced by work experience in the specific domain of the post
• 3+ years of experience in demonstrable research experience in industry or academia.
• Strong background in: TensorFlow or PyTorch; Python and packages/libraries related to computer vision or graphics; evidenced by the development of advanced applications in image/video/graphics processing or computer vision (minimum of 3 years of experience for ML engineer, minimum 5 years for Senior ML engineer),
• Evidence of leading technical developments by at least 1 research publication in a top-tier conference like CVPR, ECCV, ICCV, SIGGRAPH or similar
• Solid background in one or more of the following:

(i) neural network architectures, evidenced (for example) by knowledge of how to formulate and test advanced loss functions in neural network design;

(ii) design and test of advanced convolutional, recurrent, transformer-based, diffusion-based or other neural network architectures in a task-specific manner;

(iii) some experience in training, validation and evaluation of deep neural network models on large datasets, evidenced by experience in using Python libraries like HDF5 or similar

Desired qualifications:

• Publications, e.g. in top-tier conferences and journals: IEEE Transactions on Image Processing, IEEE Transactions on Circuits and Systems for Video Technology, conferences like IEEE CVPR/ICCV/ECCV, NeurIPS, ICML, ICLR, or similar
• Some theoretical understanding of the graphics pipeline, including coordinate transformations between frames of reference, PBR materials, rasterization, lighting, and ray tracing
• Experience in image processing theory and methods, evidenced by the development of practical designs in this area
• Some experience with 3D engines such as Unreal or Unity; in particular, generation of datasets, extraction of G-buffers, motion vectors, etc.

Benefits:

• Discretionary bonus opportunity
• Hybrid Working (within Flexmodes)
• Private Medical Insurance
• Dental Scheme
• 25 days holiday per year
• On Site Gym
• Subsidised Café
• Free soft drinks
• On site bar
• Access to cycle garage and showers

At PlayStation, Data Science plays a critical role in shaping how we invest in, retain, and delight our global player base. The CLV & Personalisation team focuses on understanding player behaviour and driving more effective engagement across the player lifecycle — from acquisition and onboarding through to retention, monetisation, and long-term value. 

As a Senior Data Scientist, you will drive the development of advanced modelling and analytical approaches that influence key commercial and product decisions at scale and are evaluated based on their impact on commercial outcomes. You will work on complex and often ambiguous problems, helping define how we measure player value and how we deliver more personalised player experiences. 

This role combines deep hands-on modelling with ownership of problem definition, approach, and impact. You will work with a high degree of autonomy across ambiguous problem spaces, shaping how data informs strategy and decision-making across the business. 

What You’ll Do 

• Design and deliver advanced machine learning models to drive player value, engagement, and growth across the lifecycle. 

• Own ambiguous problem spaces, defining modelling approaches and breaking down complex business challenges into actionable solutions. 

• Partner with senior stakeholders to shape strategies, and ensure Data Science drives high-impact decisions. 

• Apply advanced machine learning techniques, including deep learning and sequence modelling, where appropriate to capture complex player behaviours and improve model performance. 

• Evaluate and select modelling approaches based on problem context, balancing performance, scalability, and interpretability. 

• Work within cross-functional teams, including engineering, product, and commercial stakeholders, to ensure solutions are scalable, production-ready, and aligned with long-term architecture. 

• Mentor other data scientists and contribute to best practices across the team. 

• Communicate complex modelling approaches, assumptions, and outcomes clearly to senior technical and non-technical audiences. 

What We’re Looking For 

You combine technical depth in machine learning with a proactive, solution-oriented mindset, and the ability to influence strategy and inspire others. You thrive on solving sophisticated problems that deepen PlayStation’s understanding of its players and you use this understanding to inform data-driven decisions and strategies that drive player growth. 

• Proven industry experience delivering impactful, production-ready machine learning solutions in areas such as customer value, retention, or personalisation. 

• Strong expertise in modern machine learning approaches, including applying techniques such as transformers, embeddings, or sequence-based models to real-world behavioural data. 

• Ability to critically assess when advanced approaches are warranted versus simpler solutions. 

• Experience owning projects end-to-end, including problem definition, navigating ambiguity, selecting modelling approaches, and delivering impactful solutions. 

• Ability to work with large, complex datasets and translate them into scalable solutions. 

• Strong stakeholder management and communication skills, with the ability to influence decisions and communicate results persuasively to both technical and non-technical audiences. 

• Proficiency in Python, SQL, and modern ML tooling (such as Tensorflow, PyTorch, MLlib, feature stores); experience with PySpark or equivalent distributed data processing tools. 

• A strong academic background, typically a Master’s or PhD in a technical or quantitative field, specialising in Machine Learning. 

• Experience deploying models into production and maintaining business-critical or consumer facing models. 

Nice to Have 

• Background in gaming, e-commerce, or subscription-based businesses. 

• Industry experience with experimentation frameworks and causal inference. 

• Experience working in agile, fast-paced environments 

Research Engineering (Machine Learning), London 

We are looking for Research Engineers with different levels of experience - Mid through to Senior, Staff, Principal or equivalent levels.

Your impact 

This is an exciting opportunity for you to contribute to frontier research at the intersection of AI and drug design.

Working in a highly creative, iterative environment, you will be partnering with scientists and engineers to advance foundational models that will transform the biopharmaceutical world as we know it.  

You will draw upon your existing engineering and Machine Learning experience whilst learning from those around you, to apply novel techniques and ideas to newly encountered computational biology and chemistry problems.

What you will do 

Implementation & Optimisation:

• Translate research concepts into practical implementations by developing and optimising state-of-the-art AI models, and building and maintaining robust codebases, data pipelines, and infrastructure for training and evaluation.

Experimentation & Evaluation:

• Design, implement, and run experiments to evaluate the performance and robustness of ML models, using a full spectrum of state-of-the-art machine learning methods. Evaluating, tuning, and maintaining AI/ML models (which includes collecting and preparing data as needed)

Evaluation & Inference:

• Implement algorithms and software to analyse and evaluate the performance of AI models.
• Optimising performance of AI/ML models such as Diffusion models, Transformers, GNNs, leveraging a deep understanding of the AI/ML hardware+software stack
• Advise on how to bring AI/ML models to production and/or integrating them into product offerings, and monitoring and refining their behavior.
• Developing specialised tools/frameworks/infrastructure to aid in the work above

Collaboration & Knowledge Sharing:

• Work closely with research scientists and engineers, contributing to team discussions, sharing knowledge, and actively participating in code reviews to foster a collaborative environment.

Innovation & Impact:

• Proactively identify and address technical challenges, stay updated on the latest AI advancements, and focus on developing solutions that enable scaling our wider foundation and applied model platforms.
• Ability to execute on independent engineering projects and software development towards research goals.

Skills and Qualifications

Essential

• PhD in technical subject with major engineering component and exposure to AI/ML, or BSc, MSc and 2+ years of specific experience working on ML model development:
• Strong general engineering experience, as evidenced by exposure to one or more of:
• Software design / algorithms, especially for deep learning frameworks
• Modern ML frameworks such as JAX, PyTorch or TensorFlow
• Distributed systems and runtimes
• Compilers (e.g. XLA, Triton, CUDA, Pallas, …)
• Large scale model training and serving infrastructure
• Experience in navigating complex research codebases
• Databases and data processing pipelines
• Numerical methods, simulation, optimisation

• Strong fundamentals in mathematics, statistics, linear algebra
• Experience with the full ML research and development lifecycle.
• Strong understanding of ML theory and applications.
• Strong understanding of data structures and algorithms.

Nice to have

• Interest in chemistry and biology.
• Experience working with biomedical data.
• Knowledge of the pharmaceutical industry, ideally with a focus on drug discovery.

Hudson River Trading (HRT) is looking for a Senior Software Engineer to focus on our Treasury Infrastructure. Coders at HRT work on small, highly productive, and efficient teams that design, improve, and maintain the technology that powers worldwide trading — at HRT, the code you write is our business. You’ll have an opportunity to work closely with Treasury Quantitative Researchers and our Funding Team to design and develop HRT's Treasury Optimization and Research Platform.

We are looking for highly skilled programmers who love to code and solve complex problems, appreciate a culture of collaboration, and thrive in a performance-driven environment. You can always expect to be challenged by the ever-changing financial markets, and find yourself working on critical software in an extremely fast-paced, real-time environment.

Responsibilities

• Contribute to the engineering design and development of HRT’s Treasury Optimization Platform.
• Collaborate with Treasury Researchers on HRT’s Treasury Research Infrastructure.
• Collaborate with Quantitative Developers as well as our Funding and Finance teams on managing cash and collateral requirements.

Qualifications

• Completed a Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field. If you are currently pursuing your Bachelor's degree, please apply to our Campus/New Grad opportunities.
• Working experience in Python and good CS fundamentals.
• Proficiency with numerical computing libraries (Numpy, PyTorch, TensorFlow) is a plus.
• Knowledge of global portfolio financing and funding is a plus.
• Strong problem-solving skills and ability to work in a fast-paced environment.
• Excellent communication skills and ability to collaborate with engineers, researchers, and non-technical teams.

The estimated base salary range for this position is 200,000 to 300,000 USD per year (or local equivalent). The base pay offered may vary depending on multiple individualized factors, including location, job-related knowledge, skills, and experience. This role will also be eligible for discretionary performance-based bonuses and a competitive benefits package.

Who we are

Helsing is a defence AI company. Our mission is to protect our democracies. We aim to achieve technological leadership, so that open societies can continue to make sovereign decisions and control their ethical standards.

As democracies, we believe we have a special responsibility to be thoughtful about the development and deployment of powerful technologies like AI. We take this responsibility seriously.

We are an ambitious and committed team of engineers, AI specialists and customer-facing programme managers. We are looking for mission-driven people to join our European teams – and apply their skills to solve the most complex and impactful problems. We embrace an open and transparent culture that welcomes healthy debates on the use of technology in defence, its benefits, and its ethical implications.

The role

At Helsing, we are pioneering the future of autonomous decision-making for defence. Our work spans the full AI landscape, including high-volume data processing, RL agent training, and large-scale foundation models. As a member of a cross-functional team, you will architect and implement the tools and platforms that enable these breakthroughs. Your focus will be on abstracting complex distributed systems to maximise training throughput and developer velocity. We are looking for engineers who can navigate the convergence of machine learning and systems engineering to build robust, scalable platforms.

What you will do:

• Extend our highly integrated deep learning frameworks (built on top of PyTorch), making them efficient and easy to use for a wide range of use cases.

• Scale our current infrastructure and tooling stack to support faster and larger distributed training.

• Design data strategy to support large scale datasets and efficient storage, ensuring GPUs stay warm.

You should apply if you:

• Hold an MSc or PhD in Computer Science or STEM field, with a focus on Machine Learning and Deep Learning.

• Have strong software engineering skills in Python and fluency with modern DL frameworks (PyTorch/JAX/TensorFlow). You don’t just import libraries; you are comfortable writing custom layers, loss functions, and distributed training loops.

• Are a clear communicator who can build from complex theoretical concepts and contribute to the company's internal engineering culture.

• Have a "first-principles" mindset: you enjoy reading the latest AI optimisation blog posts and integrating them into codebases rapidly.

• You have debugged production ML pipelines and can tell a good war story about finding a subtle numerical or performance issue.

Note: We operate at an intersection where women, as well as other minority groups, are systematically under-represented. We encourage you to apply even if you don’t meet all the listed qualifications; ability and impact cannot be summarised in a few bullet points.

Nice to have

• You have hands-on experience training models on large-scale GPU clusters, implementing advanced parallelism strategies, and understanding the underlying cross-node communication patterns (NCCL, MPI).

• You have worked with large-scale datasets made of different modalities. Understanding the tradeoffs in locality, encoding, formats, and streaming strategies.

• You are proficient with workload orchestrators like Slurm, Kubernetes, or Ray, having used them to schedule and manage complex, concurrent training jobs at scale.

• You understand GPU architecture at a low level: memory hierarchies, warp execution, and what makes a GPU suited for training versus inference workloads.

Join Helsing and work with world-leading experts in their fields

• Helsing’s work is important. You’ll be directly contributing to the protection of democratic countries while balancing both ethical and geopolitical concerns. 

• The work is unique. We operate in a domain that has highly unusual technical requirements and constraints, and where robustness, safety, and ethical considerations are vital. You will face unique Engineering and AI challenges that make a meaningful impact in the world. 

• Our work frequently takes us right up to the state of the art in technical innovation, be it reinforcement learning, distributed systems, generative AI, or deployment infrastructure. The defence industry is entering the most exciting phase of the technological development curve. Advances in our field of world are not incremental: Helsing is part of, and often leading, historic leaps forward. 

• In our domain, success is a matter of order-of-magnitude improvements and novel capabilities. This means we take bets, aim high, and focus on big opportunities. Despite being a relatively young company, Helsing has already been selected for multiple significant government contracts.  

• We actively encourage healthy, proactive, and diverse debate internally about what we do and how we choose to do it. Teams and individual engineers are trusted (and encouraged) to practise responsible autonomy and critical thinking, and to focus on outcomes, not conformity. At Helsing you will have a say in how we (and you!) work, the opportunity to engage on what does and doesn’t work, and to take ownership of aspects of our culture that you care deeply about. 

What we offer

• Competitive salary and VSOP options
  
  
• Relocation support: up to €2,500 and 4 weeks temporary accommodation
  
  
• Learning: €500/£450 yearly allowance
  
  
• Health & wellness: gym membership and mental health support (Nilo.health)
  
  
• Social: regular company events and monthly social allowances
  
  
• Enhanced parental leave: 22 weeks fully paid for primary caregivers & 6 weeks for secondary caregivers
  
  
• Family support: 5 days of paid family emergency leave, 100% remote work option during pregnancy and phased return to work

• A hands-on onboarding program (affectionately labelled “AI-duction”), in which you will be familiarising yourself with our tools and ML pipelines used across the company. This is your opportunity to learn our tech stack, explore the company, and learn how we get things done - all whilst working with other AI and engineering teams from day one

These are the core benefits across all locations, there may be additional benefits in certain locations.

Helsing is an equal opportunities employer. We are committed to equal employment opportunity regardless of race, religion, sexual orientation, age, marital status, disability or gender identity. Please do not submit personal data revealing racial or ethnic origin, political opinions, religious or philosophical beliefs, trade union membership, data concerning your health, or data concerning your sexual orientation. 

What You’ll Do

We’re seeking a talented and experienced Senior Engineer for Network Observability to join our Network Observability team. In this role, you will be a key player in designing, developing, and maintaining the monitoring, telemetry, and observability systems that keep CoreWeave’s GPU cloud network operating reliably and at scale. You’ll focus on building solutions that provide real-time insights into network performance, ensuring that issues are detected proactively and resolved quickly.

Your mission? To empower CoreWeave’s network with advanced observability: robust metrics, powerful analytics, and automated alerting—so well-tuned that any anomalies become clear before they ever impact our customers.

• Develop, optimize, and maintain network observability platforms. Use your skills in Python and Golang to create and automate collectors, exporters, and dashboards that provide deep visibility into network health and performance.
• Collaborate with Network Engineering and Platform teams to ingest and unify logs, metrics, and events from a variety of platforms (Arista EOS, NVIDIA Cumulus Linux, Nokia SR OS, SR Linux, etc.) into a single observability pipeline.
• Design and implement scalable telemetry solutions using protocols like gNMI, SNMP, and streaming analytics. Ensure advanced alerting and anomaly detection with tools such as Prometheus, Grafana, and Alertmanager.
• Work closely with network developers, site reliability engineers, and security teams to integrate observability solutions across the broader infrastructure. Participate in design discussions, RFCs, and architectural decisions.
• Join a rotating on-call schedule to troubleshoot and resolve observability-related issues. Provide timely support to operations teams, quickly isolating and fixing problems when they arise.
• Guide junior team members, share best practices, and foster a culture of continuous learning and improvement within the observability domain.

Investing in our people is one of our top priorities, and we value candidates who can bring their diversified experiences to our teams. Here are some qualities we’ve found compatible with our team. We'd love to talk about whether this aligns with your experience and interests and what you’re excited to work on next.

Who You Are

Minimum Qualifications

• Deep familiarity with Prometheus, Grafana, Alertmanager, gNMI, and SNMP. Experience writing or extending custom metric collectors/exporters is a plus.
• Experience as a Network Engineer, SRE, Software Developer, or Systems Administrator in large-scale environments. A track record of building and operating robust telemetry and monitoring solutions is a plus.
• Passion for automating tasks and processes. You find satisfaction in creating workflows that handle repetitive tasks and reduce human error to near zero.
• Comfortable containerizing solutions in Kubernetes, designing, building, and deploying container-based workloads efficiently.
• Proficient with Python, Go, and Bash, plus familiarity with configuration management and templating tools (e.g., Ansible, Jinja2). .
• Strong knowledge of Linux systems and IP networking concepts, with hands-on experience in routing, switching, and network troubleshooting.
• Practical knowledge with a variety of platforms, including Arista EOS, NVIDIA Cumulus Linux, Nokia SR OS, and SR Linux.
• Collaborative, humble, and always ready to help others while staying open to learning from more senior colleagues.

Preferred Qualifications

• College Education: Bachelor’s degree in Computer Science or a related field.
• Machine Learning for Anomaly Detection: Hands-on experience applying ML techniques or tools (e.g., TensorFlow, scikit-learn) to proactively detect performance or security anomalies in network traffic.
• Network Certifications: Certifications like CCNA, CCNP, or similar.
• Advanced Metrics & Analytics: Hands-on experience with data pipelines, event correlation, or anomaly detection in large-scale environments.
• Distributed Tracing: Familiarity with OpenTelemetry, Jaeger, or Zipkin for end-to-end tracing across microservices and network components.

Why CoreWeave?

At CoreWeave, we work hard, have fun, and move fast!  We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values: 

• Be Curious at Your Core
• Act Like an Owner
• Empower Employees
• Deliver Best-in-Class Client Experiences
• Achieve More Together

We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and provides the opportunity to develop innovative solutions to complex problems. As we get set for take off, the growth opportunities within the organization are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us!  

The base salary range for this role is $139,000 to $204,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility). 

What You’ll Do:

The Monolith Data Science team is building a layered reliability platform that shifts CoreWeave from reactive troubleshooting to proactive reliability engineering. The platform spans telemetry ingestion, feature engineering, anomaly detection, failure prediction, distributed straggler detection, and agentic root cause analysis. As a forward deployed function, we partner closely with Fleet, Infrastructure, and AI Platform teams to embed data science directly into production environments—improving cluster reliability, increasing effective utilization (MFU), reducing MTTR, and protecting uptime and revenue.

About the role:

As a Forward Deployed Data Scientist, you will work at the intersection of data science and production systems, deploying advanced statistical models and machine learning methodologies directly within operational environments. You will collaborate closely with engineering and infrastructure teams to optimize GPU utilization, workload scheduling, and system efficiency in real time. You will design experiments, analyze large-scale system telemetry data, and build predictive and optimization solutions that are tightly integrated into production workflows. This role blends hands-on deployment with analytical rigor, turning complex infrastructure data into measurable improvements in performance and cost. You will translate research and modeling insights into scalable, production-ready systems.

Who You Are:

• MS or PhD in Computer Science, Statistics, Applied Mathematics, Machine Learning, or related quantitative field
• 8+ years (or equivalent experience) applying statistical modeling or machine learning to large-scale datasets
• Strong proficiency in Python and scientific computing libraries (NumPy, pandas, SciPy, scikit-learn, PyTorch or TensorFlow)
• Demonstrated experience designing and analyzing controlled experiments (A/B testing, causal inference, hypothesis testing)
• Experience working with distributed data systems (Spark, Ray, Dask, or similar)
• Proficiency in SQL and working with large-scale structured datasets
• Experience building, deploying, and maintaining predictive models in production environments
• Strong understanding of optimization techniques (linear programming, convex optimization, stochastic optimization, or reinforcement learning)
• Experience working with time-series data and performance telemetry
• Ability to translate analytical insights into production-ready systems and workflows
• Strong collaboration skills and ability to work cross-functionally in fast-paced environments

Preferred:

• PhD with published research in systems optimization, distributed computing, ML systems, or performance modeling
• Experience with GPU workloads, distributed training, or AI infrastructure
• Familiarity with Kubernetes, containerized workloads, or cloud-native systems
• Experience deploying reinforcement learning or adaptive scheduling systems in production
• Background in capacity planning, forecasting, or resource allocation modeling
• Contributions to open-source ML or systems projects

Wondering if you’re a good fit?
We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams—even if you aren't a 100% skill or experience match. Here are a few qualities we’ve found compatible with our team. If some of this describes you, we’d love to talk.

• You love uncovering hidden failure patterns in massive, noisy infrastructure datasets
• You enjoy working directly with engineering teams to deploy solutions that have immediate real-world impact
• You’re curious about building autonomous, agentic systems that investigate and explain system behavior
• You’re an expert in reinforcement learning, predictive modeling, or large-scale data analysis

Why CoreWeave?

At CoreWeave, we work hard, have fun, and move fast! We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values:

• Be Curious at Your Core
• Act Like an Owner
• Empower Employees
• Deliver Best-in-Class Client Experiences
• Achieve More Together

We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and enables the development of innovative solutions to complex problems. As we get set for takeoff, the organization's growth opportunities are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us!

The starting salary will be determined by job-related knowledge, skills, experience, and the market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility).

What You’ll Do

We’re seeking a talented and experienced Senior Engineer for Network Observability to join our Network Observability team. In this role, you will be a key player in designing, developing, and maintaining the monitoring, telemetry, and observability systems that keep CoreWeave’s GPU cloud network operating reliably and at scale. You’ll focus on building solutions that provide real-time insights into network performance, ensuring that issues are detected proactively and resolved quickly.

Your mission? To empower CoreWeave’s network with advanced observability: robust metrics, powerful analytics, and automated alerting—so well-tuned that any anomalies become clear before they ever impact our customers.

• Develop, optimize, and maintain network observability platforms. Use your skills in Python and Golang to create and automate collectors, exporters, and dashboards that provide deep visibility into network health and performance.
• Collaborate with Network Engineering and Platform teams to ingest and unify logs, metrics, and events from a variety of platforms (Arista EOS, NVIDIA Cumulus Linux, Nokia SR OS, SR Linux, etc.) into a single observability pipeline.
• Design and implement scalable telemetry solutions using protocols like gNMI, SNMP, and streaming analytics. Ensure advanced alerting and anomaly detection with tools such as Prometheus, Grafana, and Alertmanager.
• Work closely with network developers, site reliability engineers, and security teams to integrate observability solutions across the broader infrastructure. Participate in design discussions, RFCs, and architectural decisions.
• Join a rotating on-call schedule to troubleshoot and resolve observability-related issues. Provide timely support to operations teams, quickly isolating and fixing problems when they arise.
• Guide junior team members, share best practices, and foster a culture of continuous learning and improvement within the observability domain.

Investing in our people is one of our top priorities, and we value candidates who can bring their diversified experiences to our teams. Here are some qualities we’ve found compatible with our team. We'd love to talk about whether this aligns with your experience and interests and what you’re excited to work on next.

Who You Are

Minimum Qualifications

• Deep familiarity with Prometheus, Grafana, Alertmanager, gNMI, and SNMP. Experience writing or extending custom metric collectors/exporters is a plus.
• Experience as a Network Engineer, SRE, Software Developer, or Systems Administrator in large-scale environments. A track record of building and operating robust telemetry and monitoring solutions is a plus.
• Passion for automating tasks and processes. You find satisfaction in creating workflows that handle repetitive tasks and reduce human error to near zero.
• Comfortable containerizing solutions in Kubernetes, designing, building, and deploying container-based workloads efficiently.
• Proficient with Python, Go, and Bash, plus familiarity with configuration management and templating tools (e.g., Ansible, Jinja2). .
• Strong knowledge of Linux systems and IP networking concepts, with hands-on experience in routing, switching, and network troubleshooting.
• Practical knowledge with a variety of platforms, including Arista EOS, NVIDIA Cumulus Linux, Nokia SR OS, and SR Linux.
• Collaborative, humble, and always ready to help others while staying open to learning from more senior colleagues.

Preferred Qualifications

• College Education: Bachelor’s degree in Computer Science or a related field.
• Machine Learning for Anomaly Detection: Hands-on experience applying ML techniques or tools (e.g., TensorFlow, scikit-learn) to proactively detect performance or security anomalies in network traffic.
• Network Certifications: Certifications like CCNA, CCNP, or similar.
• Advanced Metrics & Analytics: Hands-on experience with data pipelines, event correlation, or anomaly detection in large-scale environments.
• Distributed Tracing: Familiarity with OpenTelemetry, Jaeger, or Zipkin for end-to-end tracing across microservices and network components.

Why CoreWeave?

At CoreWeave, we work hard, have fun, and move fast!  We’re in an exciting stage of hyper-growth that you will not want to miss out on. We’re not afraid of a little chaos, and we’re constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values: 

• Be Curious at Your Core
• Act Like an Owner
• Empower Employees
• Deliver Best-in-Class Client Experiences
• Achieve More Together

We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and provides the opportunity to develop innovative solutions to complex problems. As we get set for take off, the growth opportunities within the organization are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us!  

To fulfil our obligation to protect client data, successful applicants offered employment with CoreWeave will be required to complete a basic criminal record check, conducted in compliance with GDPR. Employment offers are conditional upon receiving satisfactory check results

About us:

• We are a multinational company with offices in the US (New York and Los Angeles), Germany (Berlin), and the UK (London)
• We provide a flexible work culture that offers the opportunity to collaborate and connect in person at our offices as well as accommodating work from home
• We are deeply committed to ensuring diversity, equity and inclusion at all levels of our organization and fostering a community where everyone’s voice, perspective and experience is respected and heard.
• We believe a strong team is made by investing in employees through mentorship, workshops and enrichment opportunities

Benefits:

• Not located in Berlin? No worries, we offer extensive relocation support including allowances, one way flights, temporary accommodation and, by partnering with Expath, on the ground support on arrival
• Interested in a gym membership, photography course or book? We have a Creativity and Wellness benefit!
• Employee Equity Plan
• Generous professional development allowance
• Flexible vacation and public holiday policy where you can take up to 35 days of PTO annually
• We offer free German courses at beginning, intermediate and advanced
• Various snacks, goodies, and 2 free lunches weekly when at the office

Diversity, Equity and Inclusion at SoundCloud

SoundCloud is for everyone. Diversity and open expression are fundamental to our organization; they help us lead what’s next in music by understanding and empowering our creators and fans, no matter their identity. We acknowledge the challenges in the music industry, and strive to influence an inclusive culture where everyone can contribute respectfully and thrive, especially the historically marginalized communities that many of our creators, fans and SoundClouders identify with. We are dedicated to creating an inclusive environment at SoundCloud for everyone, regardless of gender identity, sexual orientation, race, ethnicity, migration background, national origin, age, disability status, or care-giver status.

At SoundCloud you can find your community or elevate your allyship by joining a Diversity Resource Group. Diversity Resource Groups are employee-organized groups focused on supporting and promoting the interests of a particular underrepresented community in order to build a more inclusive culture at SoundCloud. Anyone can join, whether you share the identity or strive to be an ally.

About us:

• We are a multinational company with offices in the US (New York and Los Angeles), Germany (Berlin), and the UK (London)
• We provide a flexible work culture that offers the opportunity to collaborate and connect in person at our offices as well as accommodating work from home
• We are deeply committed to ensuring diversity, equity and inclusion at all levels of our organization and fostering a community where everyone’s voice, perspective and experience is respected and heard
• We believe a strong team is made by investing in employees through mentorship, workshops and enrichment opportunities

Benefits:

• Comprehensive health benefits including medical, dental, and vision plans, as well as mental health resources
• Robust 401k program
• Employee Equity Plan
• Generous professional development allowance
• Interested in a gym membership, photography course or book? We have a Creativity and Wellness benefit!
• Flexible vacation and public holiday policy where you can take up to 35 days of PTO annually
• 16 paid weeks for all parents (birthing and non-birthing), regardless of gender, to welcome newborns, adopted and foster children
• Various snacks, goodies, and 2 free lunches weekly when at the office

Diversity, Equity and Inclusion at SoundCloud

SoundCloud is for everyone. Diversity and open expression are fundamental to our organization; they help us lead what’s next in music by understanding and empowering our creators and fans, no matter their identity. We acknowledge the challenges in the music industry, and strive to influence an inclusive culture where everyone can contribute respectfully and thrive, especially the historically marginalized communities that many of our creators, fans and SoundClouders identify with. We are dedicated to creating an inclusive environment at SoundCloud for everyone, regardless of gender identity, sexual orientation, race, ethnicity, migration background, national origin, age, disability status, or care-giver status.

At SoundCloud you can find your community or elevate your allyship by joining a Diversity Resource Group. Diversity Resource Groups are employee-organized groups focused on supporting and promoting the interests of a particular underrepresented community in order to build a more inclusive culture at SoundCloud. Anyone can join, whether you share the identity or strive to be an ally.

**This is a hybrid position open to candidates in the London area, only requiring 2 days in the office**

We’re looking for a Senior Data Scientist to help build, scale, and operate production‑grade machine learning systems that power a high‑growth SaaS platform. In this role, you’ll take models from experimentation to real‑world impact—supporting real‑time decisioning, predictive analytics, and data‑driven product capabilities used by customers at scale. 

You’ll work closely with engineering, product, and data teams to deliver ML solutions that are reliable, observable, and performant in a multi‑tenant SaaS environment. 

HOW WE’LL BE WINNING TOGETHER DAY TO DAY

• Prediction models — Training and optimizing neural networks to predict eCommerce events across massive datasets 
• Real‑time inference — Designing and deploying low‑latency models with millisecond‑level time budgets 
• Production ML at scale — Building and operating ML models and web services handling 1,000+ RPS

WE SHOULD TALK IF THIS SOUNDS LIKE YOU \

• 4+ years of experience building machine learning models, with a strong emphasis on neural networks
• Strong proficiency in Python, including notebooks and production‑grade code 
• Experience in training and deploying neural network models in production environments 
• Hands‑on experience with ML frameworks such as PyTorch and TensorFlow 
• Experience building web services and APIs using Flask, FastAPI, or similar frameworks 
• Comfortable working in Linux environments, including shell scripting for monitoring and debugging applications 

DRW is a diversified trading firm with over 3 decades of experience bringing sophisticated technology and exceptional people together to operate in markets around the world. We value autonomy and the ability to quickly pivot to capture opportunities, so we operate using our own capital and trading at our own risk.

Headquartered in Chicago with offices throughout the U.S., Canada, Europe, and Asia, we trade a variety of asset classes including Fixed Income, ETFs, Equities, FX, Commodities and Energy across all major global markets. We have also leveraged our expertise and technology to expand into three non-traditional strategies: real estate, venture capital and cryptoassets.

We operate with respect, curiosity and open minds. The people who thrive here share our belief that it’s not just what we do that matters–it's how we do it. DRW is a place of high expectations, integrity, innovation and a willingness to challenge consensus.

As an AI Engineer at DRW, you will be an integral member of a collaborative multi-asset trading team. You’ll work on high-impact machine learning (ML) and artificial intelligence (AI) initiatives that are central to our business strategy. In this role, you will build critical infrastructure and tooling that leverages AI and ML technology to enhance productivity, efficiency, and discover innovative paths to challenging business and technology problems. Surrounded by cutting-edge technology and experienced trading teams, you will have the opportunity to tackle fascinating new projects while becoming a subject-matter expert in a critical and innovative role.

Key Responsibilities:

• Drive end-to-end development of AI infrastructure and AI driven applications: from initial proof-of-concept to production deployment and ongoing maintenance.
• Collaborate with technologists, traders, quantitative researchers, and data scientists to identify high-impact opportunities for integrating AI and machine learning into technology and business use cases.
• Implement automated systems for continuous training, validation, and monitoring of models, minimizing downtime and ensuring reliability.
• Provide technical leadership in selecting, integrating, and optimizing AI and ML frameworks, libraries, and tools across diverse hardware and software environments.
• Create and maintain feature pipelines, feature stores, and model stores.
• Develop frameworks to enable scalable, reproducible research.
• Proactively troubleshoot performance bottlenecks, conduct root-cause analyses, and implement solutions to optimize GPU or CPU resource usage.

Qualifications:

• Bachelor’s or advanced degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
• 3+ years of experience working with machine learning and artificial intelligence technology.
• Strong understanding of core machine learning and artificial intelligence concepts.
• Excellent programming skills in Python.
• Demonstrated experience in building, validating, deploying, monitoring, and updating production ML and AI models.
• Hands-on experience with MLOps and AIOps infrastructure and tooling.
• Proficient in problem-solving and analytical reasoning.
• Exceptional communication and collaboration skills.
• Experience with ML frameworks such as TensorFlow, PyTorch, TensorRT, or ONNX.
• Experience with Large Language Models, including RAG and fine-tuning techniques.
• Familiarity with compute infrastructure necessary to support operating AI and ML technology.

For more information about DRW's processing activities and our use of job applicants' data, please view our Privacy Notice at https://drw.com/privacy-notice.

California residents, please review the California Privacy Notice for information about certain legal rights at https://drw.com/california-privacy-notice.

#LI-BL1

Snapshot

We are seeking a Manager, Applied AI to lead the development and deployment of novel applications, leveraging Google’s generative AI models. This role focuses on rapidly developing new features, and working across partner teams to deliver solutions, and maximize impact for Google & top Google customers. You will be instrumental in translating cutting-edge AI research into real-world products, and demonstrating the capabilities of latest generation models. We are looking for a manager with a strong track record of building and shipping software, and leading engineering teams, ideally with some experience in early-stage environments, where you may have contributed to scaling products from initial concept to production. The ideal candidate will be motivated by the opportunity to drive product & business impact, and develop strong relationships with research teams.

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

This role requires a strong software engineering foundation, a passion for building and iterating on software products, and proven leadership skills. We are looking for a manager who thrives in fast-paced environments, and has the proven ability to deliver high-quality code & guide a team to success. Experience in end-to-end development is essential, as is the ability to mentor and develop junior engineers. We particularly value experience in early-stage or startup environments, where managers take ownership and drive product development from the ground up.

Key responsibilities

• Lead a team in the design and development of scalable software applications leveraging generative AI models.
• Guide the team in rapidly developing new features and iterating based on evaluation results.
• Collaborate with researchers and product managers to translate research advancements into tangible product features.
• Oversee the optimization of software performance and ensure the reliability of deployed applications.
• Champion the development of best practices for building and deploying generative AI applications.
• Lead the architecture and development of new products & features from 0 to 1.
• Mentor and develop team members, fostering a collaborative and high-performing environment.
• Partner with PM team to qualify & size new project opportunities.

About you

In order to set you up for success as a Manager, Applied AI at Google DeepMind, we look for the following skills and experience:

Required Skills

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
• 5 years of experience in a technical leadership role; overseeing projects, with 5 years of experience in a people management, supervision/team leadership role.
• 5 years of experience with one or more of the following: media generation, reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
• 7 years of experience leading technical project strategy, ML design, and optimizing industry-scale ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
• Proven experience managing software engineering teams.
• Strong software engineering skills; proficiency in Python.
• Proven experience in developing and shipping software products rapidly.
• Experience evaluating model performance, analyzing results, and implementing improvements.
• Experience with cloud computing platforms and infrastructure (e.g., Google Cloud Platform, AWS, Azure).
• Substantial experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Hugging Face, etc.
• Ability to work in a fast-paced environment and adapt to changing priorities.
• Excellent communication, collaboration, and leadership skills.

Preferred Skills

• Experience with generative AI research or applications.
• Contributions to open-source projects.
• Experience with front-end development.
• Experience working in, or founding early-stage startups.
• Experience delivering software solutions in a fast-paced, customer-facing environment.

If you are a passionate machine learning engineering leader with a drive to build innovative products and a desire to work at the forefront of AI, we encourage you to apply!

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 opportunities 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.

The Role

As a Quant Developer at Man Group you will be part of one of our flagship teams in Man’s systematic trading arm - Man AHL. The team works hand-in-hand with Quant Researchers focusing on equity market neutral models. Your challenges will be varied, and will involve building new alphas and new trading strategies.

The Team

Quant Developers at Man Group are all part of our broader technology team, members of a group of over sixty individuals representing eighteen nationalities. We have varied backgrounds including Computer Science, Mathematics, Physics, Engineering – even Classics - but what unifies us is a passion for technology and writing high-quality code.

Our developers are organised into small cross-functional teams, with our engineering roles broadly of two kinds: “Quant Platform Developers” otherwise known as our “Core Techs”, and “Quant Developers” which we often refer to as “Sector Techs”. We use the term “Sector Tech” because some of our teams are aligned with a particular asset class or market sector. People often rotate teams in order to learn more about our system, as well as find the position that best matches their interests.

 
Our Technology

Our systems are almost all running on Linux and most of our code is in Python, with the full scientific stack: numpy, scipy, pandas, scikit-learn to name a few of the open-source libraries we use extensively. We implement the systems that require the highest data throughput in Java and C++.

We use Airflow for workflow management, Kafka for data pipelines, Bitbucket for source control, Jenkins for continuous integration, Grafana + Prometheus for metrics collection, ELK for log shipping and monitoring, Docker and Kubernetes for containerisation, OpenStack for our private cloud, Ansible and Terraform for architecture automation, and Slack for internal communication. We heavily utilise ArcticDB (https://arcticdb.io/) our in-house developed DataFrame Database. Our technology list is never static: we constantly evaluate new tools and libraries.

 
Technology and Business Skills

At AHL we strive to hire only the brightest and best and most highly skilled and passionate technologists.

Essential

• Exceptional technology skills; recognised by your peers as an expert in your domain
• A keen interest and understanding of financial markets and instruments
• A proponent of strong collaborative software engineering techniques and methods: agile development, continuous integration, code review, unit testing, refactoring and related approaches
• Strong knowledge of Python
• Proficient on Linux platforms with knowledge of various scripting languages
• Experience of data analysis techniques along with relevant libraries e.g. NumPy/SciPy/Pandas
• Relevant mathematical knowledge e.g. statistics, asset pricing theory, optimisation algorithms

Advantageous

• Experience of front office quantitative software development e.g. in a hedge fund or investment bank
• Experience of web based development and visualisation technology for portraying large and complex data sets and relationships
• Experience of machine learning techniques, natural language processing and related libraries and frameworks e.g. scikit-learn, Tensorflow

 
Personal Attributes

• Strong academic record and a degree with high mathematical and computing content e.g. Computer Science, Mathematics, Engineering or Physics from a leading university
• Craftsman-like approach to building software; takes pride in engineering excellence and instils these values in others
• Demonstrable passion for technology e.g. personal projects, open-source involvement
• Intellectually robust with a keenly analytic approach to problem solving
• Self-organised with the ability to effectively manage time across multiple projects and with competing business demands and priorities
• Focused on delivering value to the business with relentless efforts to improve process
• Strong interpersonal skills; able to establish and maintain a close working relationship with quantitative researchers, traders and senior business people alike
• Confident communicator; able to argue a point concisely and deal positively with conflicting views

 
Working Here

Man Group has a small company, no-attitude feel. It is flat structured, open, transparent and collaborative, and you will have plenty of opportunity to grow and have enormous impact on what we do.  We are actively engaged with the broader technology community.

• We host and sponsor London’s PyData and Machine Learning Meetups
• We open-source some of our technology. See github.com/man-group
• We regularly talk at leading industry conferences, and tweet about relevant technology and how we’re using it. See @ManQuantTech

We’re fortunate enough to have a fantastic open-plan office overlooking the River Thames, and continually strive to make our environment a great place in which to work. We believe that agile working allows us to deliver the best business outcomes for our clients and investors as well as having a positive impact on life / work balance and the wellbeing of our staff. We are simultaneously committed to "levelling the playing field" and believe that agile working promotes inclusivity across teams, regions and business units.

• We organise regular social events, everything from photography through climbing, karting, wine tasting and monthly team lunches
• We have annual away days and off-sites for the whole team
• As well as PC’s and Macs, in our office you’ll also find numerous pieces of cool tech such as light cubes and 3D printers, guitars, ping-pong and table-football, and a piano

We offer competitive compensation, a generous holiday allowance, various health and other flexible benefits. We are also committed to continuous learning and development via coaching, mentoring, regular conference attendance and sponsoring academic and professional qualifications.

We're seeking a versatile Senior GenAI Engineer who can work across the full stack of GenAI applications, from model integration and prompt engineering to building intuitive user interfaces. You'll build production-ready AI features that empower business users to leverage the power of GenAI within their planning workflows, requiring both deep ML knowledge and strong software engineering skills. 

Your Impact  

• Develop end-to-end GenAI features, including backend API services, model integration, model monitoring, evaluations, and deployments 
• Integrate and optimize LLMs for specific use cases in business planning, including prompt engineering and RAG implementation 
• Build conversational interfaces and agentic workflows that make complex planning tasks accessible through natural language 
• Implement evaluation frameworks to measure and improve GenAI feature quality, including accuracy, latency, and user satisfaction metrics 
• Design and develop APIs that expose AI capabilities to Anaplan's platform and third-party integrations 
• Optimize model inference pipelines for performance, cost, and scalability in production environments 
• Implement monitoring, logging, and observability for GenAI systems to track usage, errors, and model behaviour 
• Collaborate with data scientists to productionize ML models and forecasting algorithms 
• Write comprehensive tests, including unit tests, integration tests, and prompt regression suites 
• Participate in code reviews, technical design discussions, and knowledge-sharing sessions 
• Stay current with GenAI research and tools, evaluating new models and techniques for potential adoption 

 Your Qualifications 

• Software engineering experience with a focus on ML/AI systems 
• Strong programming skills in Python, including experience with ML frameworks (PyTorch, TensorFlow, Transformers) 
• Experience building and deploying LLM-powered applications in production 
• Proficiency in front-end development with React, TypeScript, and modern web technologies 
• Understanding of RESTful API design, microservices architecture, and cloud infrastructure 
• Experience with prompt engineering, RAG systems 
• Strong foundation in ML fundamentals, including NLP, time-series analysis, or recommender systems 
• Familiarity with containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines 
• Excellent problem-solving skills and attention to detail 
• Bachelor's degree in computer science, Machine Learning, or related field 

Preferred Qualifications 

• Experience with GenAI frameworks (LangChain, LlamaIndex, Haystack, or similar) 
• Knowledge of vector databases (Pinecone, Weaviate, Qdrant) and embedding models 
• Experience with model serving frameworks (vLLM, TensorRT, Ray) 
• Background in forecasting, planning, or analytics applications 
• Familiarity with Anaplan or similar enterprise planning platforms 
• Experience with A/B testing and experimentation frameworks for AI features 
• Contributions to open-source ML projects or research publications 
• Experience with model observability tools (LangSmith, W&B, MLflow) 

 What Makes This Role Exciting 

• Lead a greenfield team building transformative AI capabilities from the ground up 
• Work on cutting-edge conversational and agentic AI technologies 
• Build user-facing AI features that directly impact how businesses plan and make decisions 
• Experiment with the latest GenAI models and techniques 
• Collaborate with talented engineers, data scientists, and product designers 
• Solve unique challenges at the intersection of AI and enterprise software 
• Grow your skills in both ML engineering and full-stack development 

#LI-SP1

Your Impact

We are seeking multiple highly skilled Full-Stack members of Technical Staff (MTS) to join our CoreAI organization, driving end-to-end development of AI systems across Cloud, Edge Devices, Mission Critical and Robotics platforms.

This role goes beyond pure research. You will operate across the full stack, from data, models, and infrastructure to system integration and production deployment, to deliver scalable, real-world AI solutions. You will work on cutting-edge applications spanning computer vision, NLU, multimodal AI (MLLMs), and GenAI, enabling intelligent perception, reasoning, and action in mission-critical environments.

As a senior technical leader, you will partner closely with research scientists, machine learning engineers, hardware, firmware, and product teams to translate advanced algorithms into robust, production-ready systems that operate reliably at scale.

Why This Role

You will have the opportunity to own and shape end-to-end AI systems that operate in real-world environments, bridging the gap between cutting-edge research and impactful production deployment. This role is ideal for engineers who thrive at the intersection of AI, systems, and product, and want to build scalable, high-impact solutions across cloud and edge.

What You’ll Do
Location: any cities with Axon Engineering Hub in US, Vietnam, EU (see https://www.axon.com/company)

• EU: Finland, Belgium, UK

Responsibilities

• Own end-to-end system development across data pipelines, model development, evaluation, and deployment for AI-powered products.
• Design and build scalable, production-grade systems for real-time perception, multimodal understanding, and decision-making.
• Develop and deploy models across cloud and edge environments, including resource-constrained devices.
• Architect and optimize full-stack AI pipelines, including:
• Translate research advances in computer vision, NLU, GenAI, and multimodal LLMs into production systems.
• Collaborate cross-functionally with MLE, hardware, firmware, and product teams to integrate AI into real-world systems.
• Optimize solutions for hardware-specific acceleration (GPU, NPU, DSP) and edge deployment.
• Define and drive evaluation frameworks and metrics to ensure system performance, reliability, and safety.
• Lead technical direction for complex, ambiguous problems and influence system architecture across teams.
• Contribute to technical design docs, internal knowledge sharing, and long-term platform strategy.

Basic Qualifications

• Master’s, or PhD in Computer Science, Electrical Engineering, or related field
• 8+ years (L8) or 10+ years (L9) of industry experience building production systems
• Strong programming skills in Python/C++ and experience with modern ML frameworks (e.g., PyTorch, TensorFlow)
• Proven experience delivering end-to-end systems from concept to production
• Deep expertise in one or more areas:
• Experience building and scaling distributed systems or cloud-based ML pipelines
• Experience optimizing models for latency, cost, and deployment constraints

Preferred Qualifications

• Experience deploying AI both on Cloud (AWS, AzureML), edge devices (e.g., mobile, embedded systems, robotics platforms on Qualcomm, NVIDIA, Intel)
• Familiarity with hardware acceleration frameworks (TensorRT, ONNX, SNPE, etc.)
• Experience with real-time systems and streaming data pipelines
• Knowledge of multimodal data processing (vision, audio, text, sensor fusion)
• Experience with AWS or other cloud platforms for large-scale inference and training
• Strong system design and architecture skills across cloud ↔ edge environments
• Track record of technical leadership, mentoring, and driving cross-team initiatives
• Experience in privacy-preserving AI, security, or safety-critical systems

Benefits that Benefit You

• Competitive salary and 401k with employer match
• Discretionary paid time off
• Paid parental leave for all
• Medical, Dental, Vision plans
• Fitness Programs
• Emotional & Mental Wellness support
• Learning & Development programs
• And yes, we have snacks in our offices

Benefits listed herein may vary depending on the nature of your employment and the location where you work

Location: This role is based out of our London, England office and follows a hybrid schedule. We rely on in-person collaboration and ask that team members work onsite Tuesday through Friday, with flexibility to work remotely on Mondays. We believe connection fuels innovation, and our in-office culture is designed to support meaningful teamwork and mentorship.

We are looking for an engineer with robust experience in machine learning and strong mathematical foundations to join our growing ML team and to help drive the direction of our ML platform.

Machine learning is a critical pillar of Jane Street's global business. Our ever-evolving trading environment serves as a unique, rapid-feedback platform for ML experimentation, allowing us to incorporate new ideas with relatively little friction. Our ML team is full of people with a shared love for the craft of software engineering, and for designing APIs and systems that are delightful to use. 

We’ll rely on your in-depth knowledge of the ML ecosystem and understanding of varying approaches — whether it’s neural networks, random forests, gradient-boosted trees or sophisticated ensemble methods — to aid decision-making so we apply the right tool for the problem at hand. Your work will also focus on enhancing research workflows to tighten our feedback cycles. Successful ML engineers will be able to understand the mechanics behind various modelling techniques, while also being able to break down the mathematics behind them.

If you’ve never thought about a career in finance, you’re in good company. Many of us were in the same position before working here. While there isn’t a fixed list of qualifications we’re looking for, if you have a curious mind and a passion for solving interesting problems, we have a feeling you’ll fit right in. 

We're looking for someone with:

• Experience building and maintaining training and inference infrastructure, with an understanding of what it takes to move from concept to production
• A strong mathematical background; Good candidates will be excited about things like optimisation theory, regularisation techniques, linear algebra and the like
• A passion for keeping up with the state of the art, whether that means diving into academic papers, experimenting with the latest hardware or reading the source of a new machine learning package
• A proven ability to create and maintain an organised research codebase that produces robust, reproducible results while maintaining ease of use
• Expertise wrangling an ML framework – we're fans of PyTorch, but we'd also love to learn what you know about Jax, TensorFlow or others
• An inventive approach and the willingness to ask hard questions about whether we're taking the right approaches and using the right tools
• Fluency in English required

If you're a recruiting agency and want to partner with us, please reach out to agency-partnerships@janestreet.com.

Research Scientist in Science

Founded in 2014, InstaDeep is today an EMEA leader in decision-making AI products for the Enterprise, with headquarters in London, and offices in Paris, Berlin, Tunis, Lagos, Dubai, Cape Town and the USA. InstaDeep has been named among the Top 100 global AI startups for three consecutive years by CB Insights, as well as one of the 100 most promising B2B companies in Europe, by Sifted. We have created an environment that ensures a challenge by working closely with a broad spectrum of high-quality clients, pushing you to thrive in an environment that’s rarely tedious and always looking to push you to come up with outside-the-box solutions using cutting-edge technologies. In our mission to stay ahead of the curve, we are proud to partner with firms such as BioNTech SE, Google DeepMind, NVIDIA and Intel, and world-class universities such as MIT, Oxford, UCL, and Imperial College London. We are also an NVIDIA Elite Service Delivery Partner and Google Cloud Partner.

Are you a Research Scientist in Science? You will contribute to knowledge in different fields, and plan and conduct experiments to help expand the canon of the company's scientific knowledge.

If so then keep reading…. 

As a Research Scientist in Science, you’ll be a part of the Research department, 

The Research Scientist in Science must accomplish the following:  

• Collaborate with other researchers and experts to develop machine-learning methods for problems in computational biology.
• Engage and assist in the identification of research directions
• Contribute to the design and implementation of models, tools and libraries to accelerate our research effort.
• Adapt neural network algorithms to deploy on supercomputing architectures to best exploit modern parallel environments 
• Report and present experimental results and research findings clearly and effectively, both internally and externally, verbally and in writing. 
• Contribute to the team’s publication efforts.
• Bridge the gap between the research and product teams by integrating new fundamental research into applied projects. 

Requirements:  

• Ph.D. degree in Computer Science, Machine Learning or a related field.
• Experience using Deep Learning frameworks such as PyTorch, Tensorflow and/or Jax.
• Experience in developing and debugging in Python3 or similar languages.
• Experience with high-performance computing methods and frameworks such as MPI, Ray (distribution on clusters of CPUs and accelerators)
• Experience in planning and conducting research works
• A demonstrated ability to successfully deliver high-quality research, including publishing scientific papers (ICLR, NeurIPS, ICML, etc).
• Excellent communication skills and collaborative spirit.

Nice to haves

• 2-5 years experience

• Software engineering experience demonstrated via previous work, and contributions to open source or coding competitions.
• Reinforcement Learning, Computer Vision, or Natural Language Processing experience.

Our Diversity, Equity, and Inclusion commitments

We empower individuals to celebrate their uniqueness here at InstaDeep. Our team comes from all walks of life, and we’re proud to continue encouraging and supporting applicants from underrepresented groups across the globe. Our commitment to creating an authentic environment comes from our ability to learn and grow from our diversity, and how better to experience this by other than by joining our team? 

At present, we operate in a hybrid work model of two days mandatory a week in the office. We are continuing to review the situation with the well-being of InstaDeepers at the forefront of our minds.

Right to work: Please note you will require the legal right to work in the location you are applying for. 

If you have any further questions please do not hesitate to contact us at: talent@instadeep.com

Why Engineering at Dataiku?

Dataiku’s on-premise, cloud, or SaaS-deployed platform connects many data science technologies, and our technology stack reflects our commitment to quality and innovation. We integrate the best of data and AI tech, selecting tools that truly enhance our product. From the latest LLMs to our dedication to open source communities, you'll work with a dynamic range of technologies and contribute to the collective knowledge of global tech innovators. You can find out even more about working in Engineering at Dataiku by taking a look here.

Here are some useful links so you preview what we do at Dataiku: Dataiku's Key Capabilities ; Dataiku's Github, you can also take a look at the Gallery, a public instance showcasing some example projects (note editing is very limited and will be regularly reset). 

Our product is called Dataiku DSS which stands for Dataiku Data Science Studio. If you’d like to know more about it, you can watch the demo here or try the free version here.

How you’ll make an impact

This position is either onsite/hybrid from our London office or full remote from any part of the UK.

As a Fullstack Engineer, you’ll contribute to building Dataiku DSS core features by joining one of the following themes:

• Data Preparation: Develop tools for data integration, transformation, and cataloging, as well as Jupyter notebooks, SQL workbenches, and APIs.
  • Add new capabilities for data integration, transformation, and visualization using LLMs
  • Optimize workflows for large-scale datasets and improve database support
  • Strengthen developer tools like Jupyter notebooks and SQL workbenches
  • Tech stack: Java, Python, AngularJS, Angular

• AI & Machine Learning: Collaborate on next-gen AI features, from statistics and time series forecasting to LLM inference.
• Build next-generation features like cross-provider LLM APIs or integration with the latest Machine Learning models
• Collaborate with research teams on innovative machine learning experiments
• Tech stack: Python, scikit-learn, TensorFlow, PyTorch, Java, Angular, AngularJS

• Data Consumption: build the experience that makes data accessible and actionable for everyone.
  • Enhance our collaborative Workspaces to organize and explore charts, dashboards, datasets and more
  • Create innovative interfaces that answer business questions and surface relevant insights using LLMs
  • Tech stack: Angular, AngularJS, Java, Python

• Data Visualization: elevate our data visualization capabilities with high-performance charting tools and dashboards.
  • Develop new chart types and optimize visualization performance
  • Enhance dash boarding capabilities to deliver fast and flexible experiences
  • Tech stack: React, AngularJS, Angular, D3.js, ECharts, Node.js, Java, Spring

• MLOps: Develop back-end capabilities for automating and monitoring ML model lifecycles while supporting cross-functional collaboration.
  • Build tools to automate retraining, monitoring, and deployment of ML models
  • Enhance collaboration features for ML stakeholders
  • Tech stack: Python, Java, Angular, Angular.JS, Kubernetes, Docker
    
    
• Platform: Focus on scaling and securing the platform while improving cloud integrations and supporting a wide array of data sources and engines.
  • Optimize processing engines for scalability and latency
  • Expand capabilities to support new databases and cloud platforms
  • Tech stack: Java, Python, Angular, Kubernetes, Spark, AWS, Azure, GCP
    
    
• AI Governance: Build features for AI compliance, connecting disparate systems and simplifying governance processes.
  • Develop customizable platforms for managing AI compliance and governance
  • Simplify policy enforcement and integration across disparate systems
  • Tech stack: Java, Angular, PostgreSQL

What you need to be successful 

• We’re stack agnostic, so all you need is a significant experience in software engineering,  building a real product
• We’re hiring at all levels (junior, mid, senior)
• A passion for combining backend performance with exceptional frontend user experience.
• You want to work in a fast-paced, high-growth environment that values diversity of talent, excellence of product, and exciting engineering challenges at scale

What does the hiring process look like?

• Initial call with a member of our Technical Recruiting team (45min)
• Video call with an Engineering Team Lead (1h30)
• Technical Assessment to show your skills (Home Test or Live Coding)
• Final Interviews with our VPs of Engineering (2h)   #LI-Remote

Jump Trading Group is committed to world class research. We empower exceptional talents in Mathematics, Physics, and Computer Science to seek scientific boundaries, push through them, and apply cutting edge research to global financial markets. Our culture is unique. Constant innovation requires fearlessness, creativity, intellectual honesty, and a relentless competitive streak. We believe in winning together and unlocking unique individual talent by incenting collaboration and mutual respect. At Jump, research outcomes drive more than superior risk adjusted returns. We design, develop, and deploy technologies that change our world, fund start-ups across industries, and partner with leading global research organizations and universities to solve problems.

Our AI team is a central R&D group comprised of quantitative researchers, engineers, and ML experts leading LLM research and applications at Jump. Our mission is to combine emerging techniques and models with original research to generate signals from unstructured data.

What You’ll Do: 

We are seeking research scientists with a demonstrated ability to apply machine learning to achieve state-of-the-art capabilities in complex and challenging domains. The ideal person for this role will be capable of leading an open-ended research project from concept to production: finding compelling problems well suited to current and projected LLM capabilities, collaborating extensively with trading teams to understand requirements and constraints, and continuously improving model design, tools, and infrastructure. Potential projects may target any area of the quantitative research process with the potential for firmwide application. We believe that successful research efforts require a fluid mix of skills including ML expertise, engineering pragmatism, and market intuition, and welcome all candidates who can demonstrate brilliance in one area, competence in a second, and enthusiasm for the third.

Other duties as assigned or needed.

Skills You’ll Need:

• 5+ year track record of creating ML systems with real metrics & impact in industry and/or academia
• Strong general ML background with some exposure to language modeling architectures (e.g. transformers, SSMs)
• Solid development skills in Python and/or C++
• Familiarity with ML libraries/frameworks such as PyTorch (preferred), TensorFlow, and/or JAX
• Intellectual curiosity, versatility, and originality combined with a pragmatic outlook
• Ability to reason through quantitative problems and communicate effectively with trading researchers
• Reliable and predictable availability

Bonus Points

• Experience with HPC and distributed large model training
• Experience with GPU performance optimization (CUDA or ROCm)
• Experience with end-to-end model development, especially in LLMs
• Prior academic publications and/or contributions to open-source AI research
• Strong opinions on best practices in ML research, tooling, and/or infrastructure

Miro is looking for a Machine Learning Research Engineer to serve as the technical "North Star" for our Machine Learning organization. You will operate as an Individual Contributor, driving the architectural decisions behind the "Intelligent Canvas."

Your challenge is unique in the industry: You are not just processing text. You are building models that understand spatial relationships, visual diagrams, and unstructured collaboration. You will research, prototype, and ship novel architectures that combine Large Language Models (LLMs), Computer Vision, and Graph Neural Networks (GNNs) to make Miro the smartest collaboration platform on earth.

What you’ll do

• Design, train, and ship production-grade ML models—including deep learning, NLP, and computer vision systems—that solve complex business problems and power core product features.
• Conduct deep exploratory research on massive datasets to uncover novel patterns in user behavior and content creation, translating raw data insights into new predictive modeling opportunities.
• Apply advanced fine-tuning strategies (e.g., PEFT, LoRA) to adapt state-of-the-art foundation models to specific domain tasks, rigorously experimenting to maximize performance.
• Architect scalable ML pipelines for data processing, feature engineering, training, and evaluation, ensuring high data quality and system reliability.
• Optimize model performance for latency, throughput, and resource utilization, balancing model complexity with production constraints (e.g., overfitting vs. underfitting, compute efficiency).
• Collaborate cross-functionally with data engineers, product managers, and software engineers to translate business requirements into technical ML specifications and integrate models into user-facing applications44.
• Champion MLOps excellence by automating deployment workflows, implementing CI/CD for ML, and establishing robust monitoring for model drift and health.
• Stay at the forefront of ML research, evaluating novel algorithms and techniques (e.g., Transformer architectures, quantization) to drive innovation and technical strategy.

What you’ll need

• Strong foundation in ML theory and statistics, including hypothesis testing, probability distributions, regression, classification, and optimization techniques.
• Solid engineering fundamentals. You are comfortable writing production-level Python and have a deep understanding of data structures, algorithms, and distributed system design.
• Deep proficiency in Python and the modern ML stack, with hands-on experience using libraries like Pandas, NumPy, Scikit-learn, and deep learning frameworks (PyTorch, TensorFlow).
• Gradient Debugging: Expertise in PyTorch or JAX, including experience with distributed training (e.g., DDP, FSDP) and debugging complex gradient issues.
• Applied Research: Ability to read, implement, and improve upon the latest academic papers (NeurIPS, ICML, CVPR). You don't just use libraries; you understand the math underneath them and can reproduce results in peer-reviewed papers.
• Track record of end-to-end ML delivery, from exploratory data analysis (EDA) and feature engineering to training, validation, and deploying models in a production environment.
• Experience with large-scale systems, capable of designing resilient architectures that handle vast datasets and high-throughput inference requests.
• Strong engineering mindset, valuing code quality, testing, modularity, and maintainability just as highly as model accuracy.

Education + Experience

• Option A: Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, or related field plus ~3+ years of professional ML engineering experience.
• Option B: No formal degree, ~6+ years of industry experience demonstrating equivalent proficiency in building and shipping ML systems.

What's in it for you

LON:

• Competitive equity package
• Health insurance for you and your family
• Corporate pension plan
• Lunch, snacks and drinks provided in the office
• Wellbeing benefit and WFH equipment allowance
• Annual learning and development allowance to grow your skills and career
• Opportunity to work for a globally diverse team
  

Multi Location: Amsterdam / Berlin / Yerevan / London:

• Competitive equity package
• Lunch, snacks and drinks provided in the office
• Wellbeing benefit and WFH equipment allowance
• Annual learning and development allowance to grow your skills and career
• Opportunity to work for a globally diverse team

Recruiter: #LI-MH1

About the Role

JOB RESPONSIBILITIES:

A highly collaborative, fast-growing team at Internal Alpha Capture (IAC), Point72 is developing AI-driven equity trading signals that leverage rigorous research, state-of-the-art machine learning methods, proprietary data sources, and unparalleled computing power.

We are looking for exceptional machine learning researchers to join our efforts. Researchers will work closely with our experienced team members and apply the full breadth of their machine learning knowledge to unique, proprietary datasets, and develop novel trading signals that have high impact. Prior experience in the financial industry is not required.

Key responsibilities may include:

• Managing all aspects of the research process, including ideation, method selection, implementation, evaluation, and eventual application.
• Identifying, adapting, and extending existing models in the broad field of machine learning; conducting novel research as needed, to develop new signals that can enhance portfolio returns, or predict other variables of interests.
• Staying up to date on the advances in AI/ML and related technological innovations to provide recommendations on new models and tools and identify emerging opportunities.

DESIRABLE CANDIDATES:

• Master’s or PhD in machine learning, computer science, statistics, or related fields.
• Knowledge and experience in any of the following areas are strongly preferred: modern sequence models, graph neutral nets, reinforcement learning, LLMs.
• Prior research experience utilizing machine learning over large, possibly noisy, data sets.
• Strong analytical and quantitative skills, and a detail-oriented mindset.
• Strong proficiency in machine learning libraries such as Torch, JAX or TensorFlow.
• Competence in Python, cluster environment, and general software engineering principles (source control, testing, collaborative workflow).
• Excellent written and verbal communication skills, willing to proactively engage other team members in helping to foster a highly collaborative, team-oriented research environment.
• Commitment to the highest ethical standards.

We are hiring a Principal Machine Learning Engineer to work on cutting-edge R&D and translating research into customer-centric solutions.   

As innovators in speech technology, our mission is to Understand Every Voice—a vision that has propelled us to be world leaders of Voice AI. Fuelled by innovation, inclusivity, and a passion for making a global impact through world-leading Speech AI, we're looking for an experienced Principal Machine Learning Engineer to accelerate our efforts towards exceptional speech solutions. 

Our Modelling Team trains diverse models, including large self-supervised ones, supporting Speechmatics towards being the most accurate speech recognition system globally. It also ensures their deployment into production, working with the latest developments in ML, but also with the best engineering practices for software engineering and model serving. 

This is a hands-on, technical leadership role with high ownership.  You will develop and deploy advanced speech systems that power our products as well as co-define the technical vision for ML, drive innovation, and mentor engineering teams. Your work will span the entire codebase.    

What You’ll Do:

• Develop and deploy ML models, translating research into scalable, maintainable code and services 
• Optimise ML models for speed, accuracy, and cost efficiency 
• Evaluate and integrate cutting-edge approaches into our ML stack
• Identify and solve complex ML problems across the organisation
• Define and enforce best practices for code quality, model lifecycle management, etc.
• Mentor engineers and foster a culture of technical excellence and innovation
• Co-define the long-term technical vision 

What We’re Looking For:

• Deep understanding of the modern Machine Learning stack, for example:
  • Knowledge of contemporary transformer architectures (e.g., GQA, KV-caching) and best practices
  • Expertise in distributed training techniques
  • Familiarity with optimisation strategies for model inference (e.g., dynamic batching, flash attention, speculative decoding)
• Proven track record of developing and deploying models at scale
• Expertise in Python, ML frameworks (TensorFlow, PyTorch), and experience with cloud platforms
• Strong familiarity with MLOps principles, CI/CD pipelines, and containerization (Docker, Kubernetes)

  With preferred backgrounds covering some of the following:

• Experience with speech-to-text or text-to-speech 
• Contributions to open-source projects or published research in top-tier conferences

We are hiring a Principal Machine Learning Engineer to work on cutting-edge R&D and translating research into customer-centric solutions.   

As innovators in speech technology, our mission is to Understand Every Voice—a vision that has propelled us to be world leaders of Voice AI. Fuelled by innovation, inclusivity, and a passion for making a global impact through world-leading Speech AI, we're looking for an experienced Principal Machine Learning Engineer to accelerate our efforts towards exceptional speech solutions. 

Our Modelling Team trains diverse models, including large self-supervised ones, supporting Speechmatics towards being the most accurate speech recognition system globally. It also ensures their deployment into production, working with the latest developments in ML, but also with the best engineering practices for software engineering and model serving. 

This is a hands-on, technical leadership role with high ownership.  You will develop and deploy advanced speech systems that power our products as well as co-define the technical vision for ML, drive innovation, and mentor engineering teams. Your work will span the entire codebase.    

What You’ll Do:

• Develop and deploy ML models, translating research into scalable, maintainable code and services 
• Optimise ML models for speed, accuracy, and cost efficiency 
• Evaluate and integrate cutting-edge approaches into our ML stack
• Identify and solve complex ML problems across the organisation
• Define and enforce best practices for code quality, model lifecycle management, etc.
• Mentor engineers and foster a culture of technical excellence and innovation
• Co-define the long-term technical vision 

What We’re Looking For:

• Deep understanding of the modern Machine Learning stack, for example:
  • Knowledge of contemporary transformer architectures (e.g., GQA, KV-caching) and best practices
  • Expertise in distributed training techniques
  • Familiarity with optimisation strategies for model inference (e.g., dynamic batching, flash attention, speculative decoding)
• Proven track record of developing and deploying models at scale
• Expertise in Python, ML frameworks (TensorFlow, PyTorch), and experience with cloud platforms
• Strong familiarity with MLOps principles, CI/CD pipelines, and containerization (Docker, Kubernetes)

  With preferred backgrounds covering some of the following:

• Experience with speech-to-text or text-to-speech 
• Contributions to open-source projects or published research in top-tier conferences

Research Scientist (Machine Learning), Lausanne

Your impact 

As a Research Scientist in machine learning (ML), you will play an exciting role in building greenfield machine learning based models and algorithms that will power our platform to transform the drug discovery world as we know it. 

Working in a highly creative, fast-paced and interdisciplinary environment, you will be partnering with leading engineers and scientists to conceive, design, and develop cutting edge machine learning algorithms to unlock new modelling and predictive power which will be critical to the organisation’s success. You will draw upon your existing deep research experience whilst learning from those around you, to apply novel techniques and ideas to newly encountered computational biology and chemistry problems.

Depending on your experience:

You will create and lead projects, bringing together a variety of disciplined scientists and engineers to pursue some of the most ambitious modelling problems with deep learning - as well as providing technical mentorship and people management for others in the ML community at Isomorphic Labs

You will be instrumental in leading greenfield machine learning based research projects, building the models, and algorithms that will power our platform to transform the drug discovery world as we know it.

What you will do

• Contribute to our research directions in machine learning by using your extensive knowledge of the field to apply world-leading ML algorithms to drug discovery.
• Identify and create novel ML techniques and the required data to train.
• Develop the architectures and training algorithms of machine learning models.
• Analyse and tune experimental results to inform future experimental directions.
• Implement and scale training and inference engineering frameworks.
• Report and present research findings and developments clearly and efficiently, to both other ML scientists and scientists of different disciplines.
• Iterate collaboratively with scientists and domain experts, sharing your own domain experience.
• Suggest and engage in team collaborations to meet ambitious research goals.
  
  Depending on your experience:
• Provide technical mentorship and guidance to the ML research community, advising on projects, and shaping our research roadmap based on your deep technical expertise.
• Provide developmental support to other ML research scientists.
• Create, lead, and run ML research projects, fostering collaborative and diverse teams to solve high priority modelling problems.Cultivate a diverse and inclusive research culture.

Skills and qualifications 

Essential

• PhD or equivalent practical experience in a technical field.
• A proven track record in machine learning using deep learning techniques, including designing new architectures, hands-on experimentation, analysis, and visualisation.
• Strong knowledge of linear algebra, calculus and statistics.
• Experience using ML frameworks such as JAX, PyTorch, or TensorFlow, and scientific software such as NumPy, SciPy, or Pandas.
• A passion for applying ML research to real world problems.
• Depending on your experience: project supervision, leadership, or management.

Nice to have

• PhD in machine learning or computer science.
• Relevant research experience to the position such as post doctoral roles, a proven track record of publications, or contributions to machine learning codebases.
• Experience working in a scientific environment across disciplines (particularly biology, chemistry, physics).
• Experience working with biological or chemical data and biological or chemistry software.
• Experience working with real-world datasets.
• Experience with ML on accelerators.
• Experience in any of: large scale deep learning, generative models, graph neural networks, deep learning for drug discovery, deep learning for computer vision, 3D graphics/robotics, real-world applied RL.

Research Scientist (Machine Learning), London

Your impact 

As a Research Scientist in machine learning (ML), you will play an exciting role in building greenfield machine learning based models and algorithms that will power our platform to transform the drug discovery world as we know it. 

Working in a highly creative, fast-paced and interdisciplinary environment, you will be partnering with leading engineers and scientists to conceive, design, and develop cutting edge machine learning algorithms to unlock new modelling and predictive power which will be critical to the organisation’s success. You will draw upon your existing deep research experience whilst learning from those around you, to apply novel techniques and ideas to newly encountered computational biology and chemistry problems.

Depending on your experience:

You will create and lead projects, bringing together a variety of disciplined scientists and engineers to pursue some of the most ambitious modelling problems with deep learning - as well as providing technical mentorship and people management for others in the ML community at Isomorphic Labs

You will be instrumental in leading greenfield machine learning based research projects, building the models, and algorithms that will power our platform to transform the drug discovery world as we know it.

What you will do

• Contribute to our research directions in machine learning by using your extensive knowledge of the field to apply world-leading ML algorithms to drug discovery.
• Identify and create novel ML techniques and the required data to train.
• Develop the architectures and training algorithms of machine learning models.
• Analyse and tune experimental results to inform future experimental directions.
• Implement and scale training and inference engineering frameworks.
• Report and present research findings and developments clearly and efficiently, to both other ML scientists and scientists of different disciplines.
• Iterate collaboratively with scientists and domain experts, sharing your own domain experience.
• Suggest and engage in team collaborations to meet ambitious research goals.
  
  Depending on your experience:
• Provide technical mentorship and guidance to the ML research community, advising on projects, and shaping our research roadmap based on your deep technical expertise.
• Provide developmental support to other ML research scientists.
• Create, lead, and run ML research projects, fostering collaborative and diverse teams to solve high priority modelling problems.Cultivate a diverse and inclusive research culture.

Skills and qualifications 

Essential

• PhD or equivalent practical experience in a technical field.
• A proven track record in machine learning using deep learning techniques, including designing new architectures, hands-on experimentation, analysis, and visualisation.
• Strong knowledge of linear algebra, calculus and statistics.
• Experience using ML frameworks such as JAX, PyTorch, or TensorFlow, and scientific software such as NumPy, SciPy, or Pandas.
• A passion for applying ML research to real world problems.
• Depending on your experience: project supervision, leadership, or management.

Nice to have

• PhD in machine learning or computer science.
• Relevant research experience to the position such as post doctoral roles, a proven track record of publications, or contributions to machine learning codebases.
• Experience working in a scientific environment across disciplines (particularly biology, chemistry, physics).
• Experience working with biological or chemical data and biological or chemistry software.
• Experience working with real-world datasets.
• Experience with ML on accelerators.
• Experience in any of: large scale deep learning, generative models, graph neural networks, deep learning for drug discovery, deep learning for computer vision, 3D graphics/robotics, real-world applied RL.

Research Scientist - Applied Large Language Models 

Your impact 

As a Research Scientist focused on the application of Large Language Models (LLMs), you will play an exciting role in bringing cutting edge technologies to bear across our research areas to transform the drug discovery world as we know it. 

Working in a highly creative, fast-paced and interdisciplinary environment, you will be partnering with leading research scientists and engineers to conceive, design, and develop cutting edge LLM applications that help to unlock new modelling capabilities and predictive power which will be critical to the organisation’s success. You will draw upon your existing deep understanding and experience whilst learning from those around you, to apply novel techniques and ideas to newly encountered computational biology and chemistry problems.

Depending on your experience:

You will both partner with teams across our existing research areas and create and lead standalone projects, bringing together a variety of disciplined scientists and engineers to pursue some of the most ambitious modelling problems through the application of LLMs - as well as providing technical mentorship and people management for others in the ML community at Isomorphic Labs.

You will be instrumental in leading machine learning based research projects, building the models, and algorithms that will power our platform to drive us close to achieving our ambitious mission to one day solve all disease with the help of AI.

What you will do

• Contribute to core research in machine learning by pushing the boundaries of Large Language Models in their application to the world of drug discovery
• Develop and refine LLM-driven approaches for multiple use cases across our research areas, using your extensive knowledge of the field to modify and apply models and explore their capabilities when applied to complex biological and medical challenges.
• Identify and create novel ML techniques and the required data to train and apply models
• Analyse and tune experimental results to inform future experimental directions.
• Implement and scale training and inference engineering frameworks
• Report and present research findings and developments clearly and efficiently, to both other ML scientists and scientists of different disciplines
• Iterate collaboratively with scientists and domain experts, sharing your own domain experience
• Suggest and engage in team collaborations to meet ambitious research goals
  
  Depending on your experience:
• Provide technical mentorship and guidance to the ML research community, advising on projects, and shaping our research roadmap based on your deep technical expertise.
• Provide developmental support to other ML research scientists.
• Create, lead, and run ML research projects, fostering collaborative and diverse teams to solve high priority modelling problems. Cultivate a diverse and inclusive research culture.

Skills and qualifications 

Essential

• PhD or equivalent practical experience in a technical field
• Highly specialized LLM builder with a passion for, and strong experience in, applying LLMs to novel problem spaces
• Deep understanding and experience of model architectures, training methods, and techniques for application of LLMs, including deployment for bespoke use cases and applications, established experience in post-training, reasoning, test-time scaling, tool-use, alignment, agents, LLM research, as well as reinforcement learning and fine-tuning 
• Strong knowledge of linear algebra, calculus and statistics.
• Experience using ML frameworks such as JAX, PyTorch, or TensorFlow, and scientific software such as NumPy, SciPy, or Pandas.
• Depending on your experience: project supervision, leadership, or management.
• Strong knowledge of LLM landscape today, and likely developments for the near future
• Experience working with real-world datasets.

Nice to have

• PhD in machine learning or computer science.
• Relevant research experience to the position such as post doctoral roles, a proven track record of publications, or contributions to machine learning codebases.
• A strong background in biology or medicine, enabling you to bridge the gap between advanced AI capabilities and complex scientific problems in drug discovery
• Experience working in a scientific environment across disciplines (particularly biology, chemistry, physics), and with real world biological or chemical datasets and biological or chemistry software
• Experience in computational chemistry, bioinformatics, or related fields would be highly beneficial, along with a track record of applying AI to real-world scientific challenges
• Experience with multi-parameter optimization
• Experience in any of: large scale deep learning, generative models, graph neural networks, deep learning for drug discovery, deep learning for computer vision, 3D graphics/robotics, real-world applied RL

About the Team

Miro is on a mission to empower teams to create the next big thing, and our teams are at the forefront of making that vision a reality. Our teams drive AI-powered innovation across Miro's platform by building robust technical foundations, delightful product features, and intelligent capabilities that transform how users interact with content on the canvas. Whether developing structured widget capabilities that help users visualize and interact with complex information, building AI platform infrastructure, or creating intelligent features that anticipate user needs, our work is foundational to Miro's evolution.

About the Role

As an AI Engineer, you'll design and build AI-driven capabilities that enhance how users create, transform, and collaborate on canvas. You'll bridge AI innovation and product delivery - shipping delightful, safe, and reliable experiences that leverage cutting-edge LLMs while maintaining the performance and polish users expect from Miro's collaborative canvas.

What you’ll do

• Design, develop, and ship AI-driven capabilities—including agents, intelligent assistants, context-aware prediction, and generative AI—using Python, top-tier LLMs, TypeScript, React, Canvas, and WebGL
• Engineer high-performing AI workflows leveraging LLMs (OpenAI, Anthropic Claude, Google Gemini), prompt engineering, and generative techniques—ensuring reliability, scalability, and maintainability
• Execute end-to-end AI projects from conceptualization and prototyping to production code, collaborating closely with product managers, designers, and engineers
• Experiment and iterate on AI capabilities within your team domain, staying ahead of emerging AI tools, frameworks, and techniques
• Champion best practices in AI system development—including evaluations, LLMOps, CI/CD, observability, and ethical AI principles
• Measure and optimize AI performance, establishing benchmarks for user engagement, model accuracy, latency, error rate, and drift
• Write clean, well-tested, maintainable code, participating in code reviews and® technical discussions across the stream
• Troubleshoot and resolve production issues, ensuring high availability and performance

What you’ll need

• 3+ years of professional experience with a proven track record delivering AI-first capabilities in customer-facing products—driving value through features users directly interact with
• Excellent communication skills, able to translate complex technical concepts for non-technical stakeholders
• Strong Python skills and familiarity with FE technologies (e.g. Typescript, React etc)
• Demonstrated expertise in prompt engineering and context engineering using top-tier LLMs (OpenAI GPT, Anthropic Claude, Google Gemini)
• Ability to develop high-quality, production-ready code within complex codebases
• Experience with LLM evaluation frameworks and a track record of building evals that meaningfully inform model selection, prompt iteration, or feature quality.
• Solid understanding of ML fundamentals, including probabilistic modeling, evaluation techniques, and deep neural networks
• Experience with LLMOps and cloud services (AWS, Azure, Amazon Bedrock, etc.)
• AI-First Proficiency. We’re building for an AI-first future, and we’re looking for graduates who aren’t just using AI—they’re mastering it. We’re excited to meet early-career engineers who have moved beyond simple chat prompts and have truly integrated AI into their development flow. Whether it’s using AI agents for autonomous debugging, analyzing logs, or rapidly prototyping and shipping features to production, we value the ability to "pilot" these tools to deliver high-quality code at an ambitious pace.
• Nice-to-have: Experience with rendering technologies like WebGL, Canvas API, or 2D graphics libraries (PixiJS, Skia)
• Nice-to-have: Real-time technologies experience (WebSocket)
• Nice-to-have: Vector databases, RAG pipelines, LangChain, or agent frameworks
• Nice-to-have: Multi-modal AI or long-context handling
• Nice-to-have: ML frameworks: PyTorch, TensorFlow, Hugging Face Transformers

What's in it for you

We want you to feel supported, connected, and ready to grow. Our global benefits package generally includes equity, a wellbeing benefit, a WFH equipment allowance, and an annual Learning & Development stipend. Join a diverse team where you can do your best work. Full benefits may differ per location. If you would like to learn more about location-specific benefits, please refer to our Global Miro benefits board.

Recruiter: #LI-JR1

At AKQA (part of WPP), we believe in the imaginative application of art and science to create beautiful ideas, products and services. With an entrepreneurial and collaborative approach, we design and build adaptive digital products, services and experiences that capture the imagination and deliver impressive returns for our clients.

Our roles and responsibilities are rapidly changing during this age of rapid AI growth, adoption, capability and market options.  AI Landscape and Production AI implementation experience is essential.

The Technical Lead is the main driver for the end-to-end; ideation, technical innovation, design, scoping, development, deployment and maintenance of solutions using the latest tools and technologies.  The Technical Lead has overall responsibility for the day-to-day technical ownership and direction of a project.

While this role is client-facing and involves leading the technical direction, you will also be expected to lead the architecture of the project and will contribute to code, particularly during critical phases or to prototype new features.  

You will be working closely with Business, Project Management, Creative, UX, and Data teams whilst also running on-shore, off-shore and hybrid development teams. 

This role also involves contributing to Technical Strategy, ideation, pitching, pre-sales activities and engineering, thought leadership, profile creation and speaking engagements.

Based in London (Farringdon), in a Hybrid working environment, frequently collaborating with our global studios and partners, you will enjoy working in a team of highly skilled people, all with strong opinions about various technologies, frameworks and approaches. 

You will articulate your ideas to colleagues effectively whilst also taking on board the ideas of others and remaining solutions focused. You will thrive when faced with new challenges, view them as opportunities and constantly look to improve client offerings. You will work in a progressive environment that fosters a meritocratic culture, surrounded by some of the brightest minds in their fields. 

As a Technical Lead at AKQA, you will be inspired by technology and have a passion for creating innovative solutions.

While you may from time-to-time, also be asked to wear the hats of a Project Manager, Scrum-Master or Product Owner; we are looking for a Technologist first, with these additional capabilities. 
Technical Architecture and Engineering capability and experience is mandatory.

ROLE REQUIREMENTS

• Client facing.
• Thought Leadership and promotion of AKQA Technology.
• AI Implementor
• AI Usage - proficient elevated workflow and development tooling
• AI Enabled Experience Development & Integration - vendor and cloud landscape knowledge, systems design, integration & model customisation - with proven experience of addressing marketing challenges such as content generation, personalisation, campaign optimisation etc.
• AI Architecture - Agentic AI creation and Orchestration.
• AI Content & Data Engineering - experience of collecting, cleansing, transforming and embedding.
• AI Cost x Value calculations.
• AI Governance and Testing models
• Design and implement first-class end-to-end Solutions and MACH Architectures.
• Ability to create prototypes or bug fixes.
• Ability to integrate innovative solutions into the technical architecture.
• Ability to analyse, appraise and make recommendations, taking into account existing client technology landscape whilst pushing new technology solutions to align with business ambitions.
• Ability to evaluate and validate the technical complexities of multi-tiered web solutions and systems integration, their underlying technologies and the latest technical tools.
• Ability to gather requirements and break them down into the technical tasks required to complete a project phase.
• Ability to operate within different software delivery methodologies such as Lean Innovation teams, KANBAN and larger SCRUM teams.
• Ability to recognise technical risk and plan to mitigate, and/or move fast to solutionise.
• Able to decide the resource profile required for a project and to provide top-down and bottom-up estimates against a scope.
• Line manage and coach Developers and help them to grow and develop their careers and capabilities.
• Ability to manage one or two; onshore, nearshore, offshore or hybrid development team(s) at a time.
• Strive to learn new skills and stay abreast of technical developments, successfully applying them to work practices.
• Ability to compare and select the most appropriate supplier or product for the required task.
• Ability and techniques to improve processes per project, client workstreams and in the technology department as a whole.
• Technical skills and knowledge:
• Cloud hosting providers such as AWS, Azure, GCP, Vercel & Netlify
• Cross-platform AI experience across AWS, Microsoft Azure, Google (e.g. Bedrock, AgentCore, Vertex, Azure ML etc.)
• Advanced Python programming
• AI frameworks such as AutoGen, Langflow, Tensorflow
• Knowledge of Infrastructure as Code, CI/CD
• Use of Middleware and RESTful or GraphQL APIs
• Microservices and MACH Architectures.
• HTML, CSS, Javascript frameworks such as React,
  or Mobile technologies such as SwiftUI, Kotlin, Flutter or React-native
• CMS, DXPs and common MarTech
• SaaS products integration
• Atlassian, Azure DevOps, GitLab or similar workflow tools
• Understanding of Automation and Quality assurance practices

QUALITIES AND CHARACTERISTICS 

• Must be from an engineering or development background.
• A continuous-improvement approach to management.
• Proactive self-starter with acute attention to detail and drive for improvement.
• A practically-minded thought leader whose first priority is delivering excellent work. 
• Advocate for improvements to processes, quality, and security.
• Analytical and positive mindset with a personable and professional approach.
• Sharp attention to detail and a passion for new technology, staying abreast with the latest developments in the industry.
• Professional written and verbal communication.
• Be able to talk about Technology to non-technical audiences (clients, stakeholders and team members).
• Champion continuous improvement and best-in-class software development processes.
• Contribute to the ideation process and be proactive in proposing technical solutions to needs that other disciplines may not be aware of.

Explore our extensive range of benefits here.

835 - Manager, Client Analytics - DTA

About WPP Media 

WPP is the creative transformation company. We use the power of creativity to build better futures for our people, planet, clients and communities. For more information, visit wpp.com. 

WPP Media is WPP’s global media collective. In a world where media is everywhere and in everything, we bring the best platform, people, and partners together to create limitless opportunities for growth. For more information, visit wppmedia.com 

At WPP Media, we believe in the power of our culture and our people. It’s what elevates us to deliver exceptional experiences for both our clients and each other. In this role it will be critical to embrace WPP & WPP Media’s shared core values: 

• Be Extraordinary by Leading Collectively to Inspire transformational Creativity. 

• Create an Open environment by Balancing People and Client Experiences by Cultivating Trust. 

• Lead Optimistically by Championing Growth and Development to Mobilize the Enterprise. 

About Choreograph: A Leading WPP Media Brand 

Choreograph is WPP’s global data products and technology company. We’re on a mission to transform marketing by building the fastest, most connected data platform that bridges marketing strategy to scaled activation. 

We work with agencies and clients to transform the value of data by bringing together technology, data and analytics capabilities. We deliver this through the Open Media Studio, an AI-enabled media and data platform for the next era of advertising. 

We’re endlessly curious. Our team of thinkers, builders, creators and problem solvers are over 1,000 strong, across 20 markets around the world. 

Role Summary and Impact   

The Manager, Client Analytics reports to the Director of Analytics, working to design, customize and maintain platforms for business analytics and measurement. You would have excellent oral and written communication skills, be client obsessed, self-motivated and able to operate both as a team and independently with limited guidance and direction

The Manager, Client Analytics is following the direction of Director of Analytics and is responsible for data manipulation and visualization, performing quantitative data analysis, problem solving, statistical modeling, and developing/analysing business cases.

WHAT YOU WILL DO   

• Apply deep knowledge of basic statistics (significance testing, correlation analysis, confidence intervals, descriptive statistics) to support analytical solutions.
• Use statistical modeling techniques (regression, classification) to extract business value from campaign data.
• Utilize programming languages (Python, R, SQL), statistical packages (SciPy), and Google tools (BigQuery, Tensorflow, Datalab) to prototype and deliver data-driven solutions.
• Recommend and develop technical solutions with guidance from senior leadership.
• Define project scope, setup, and effort estimation in collaboration with the account Analytics lead.
• Build and maintain strong relationships with Analytics leads and gain a deep understanding of client challenges.
• Work closely with key stakeholders to assess project needs and ensure delivery of best-in-class analytics work.
• Collaborate with regional leadership on process development, improvement, and compliance.
• Support campaign measurement, determine incremental lift from marketing activities, and manage reporting and data needs (ingestion, cleaning, delivery).
• Code in SQL and Python to create reports and build dashboards; automate recurring workloads to improve efficiency.
• Generate meaningful insights using advanced analytics/statistical techniques; create dashboards and presentations for wider teams.
• Ensure continuous collaboration and progression across bands, disciplines, and offices.

Skills and Experience  

• Relevant industry experience in analytics-focused roles.
• Degree in an applied quantitative field (data science, mathematics, statistics, engineering, economics, business management, computer science, or related).
• Understanding of marketing campaigns, objectives, and measurement techniques; prior experience in digital agency or consulting preferred.
• Proficient coding skills in statistical software (R, Python, SciPy), programming languages (SQL, Python), and MS Office tools (especially advanced Excel/Google Sheets).
• Experience in owning and delivering analytics projects, including correlation, regression, significance testing, A/B tests, and supervised machine learning.
• Practical understanding of data science techniques, statistical analysis, and modeling.
• Passion for data analysis, troubleshooting data anomalies, integrating data from multiple sources to create repositories for data science models.
• Ability to transform raw data into actionable business insights for decision-making and strategic planning.
• Strong logical thinking, problem-solving, and stakeholder management skills.
• Excellent verbal and written communication skills.
• Adherence to quality standards and ability to plan and prioritize work.
• Experience using or building reports with business intelligence tools is a plus.
• Experience in applying big data, statistics, and analytical techniques to solve client problems is preferred.
• Business acumen to provide actionable strategic recommendations is preferred

Life at WPP Media & Benefits 

Our passion for shaping the next era of media includes investing in our employees to help them do their best work, and we’re just as committed to employee growth as we are to responsible media investment. WPP Media employees can tap into the global WPP Media & WPP networks to pursue their passions, grow their networks, and learn at the cutting edge of marketing and advertising. We have a variety of employee resource groups and host frequent in-office events showcasing team wins, sharing thought leadership, and celebrating holidays and milestone events. Our benefits include competitive medical, group retirement plans, vision, and dental insurance, significant paid time off, preferential partner discounts, and employee mental health awareness days.   

WPP Media is an equal opportunity employer and considers applicants for all positions without discrimination or regard to characteristics. We are committed to fostering a culture of respect in which everyone feels they belong and has the same opportunities to progress in their careers. 
 
We believe the best work happens when we're together, fostering creativity, collaboration, and connection. That's why we’ve adopted a hybrid approach, with teams in the office around four days a week. If you require accommodations or flexibility, please discuss this with the hiring team during the interview process. 

Please note this is a UK based role and requires individuals to have the right to work in this location

Please read our Privacy Notice (https://www.wppmedia.com/pages/privacy-policy) for more information on how we process the information you provide. 

#LI-Promoted

1211 - Director, Data Science - DTA

About WPP Media

WPP is the creative transformation company. We use the power of creativity to build better futures for our people, planet, clients and communities. For more information, visit wpp.com.

WPP Media is WPP’s global media collective. In a world where media is everywhere and in everything, we bring the best platform, people, and partners together to create limitless opportunities for growth. For more information, visit wppmedia.com

About Choreograph: A Leading WPP Media Brand

Choreograph is WPP’s global data products and technology company. We’re on a mission to transform marketing by building the fastest, most connected data platform that bridges marketing strategy to scaled activation.

We work with agencies and clients to transform the value of data by bringing together technology, data and analytics capabilities. We deliver this through the Open Media Studio, an AI-enabled media and data platform for the next era of advertising.

We’re endlessly curious. Our team of thinkers, builders, creators and problem solvers are over 1,000 strong, across 20 markets around the world.

Role Summary and Impact

The Data Science Director, plays a critical leadership role as part of a broader team in the deployment and development of predictive models for our customers. You will lead and mentor a team, working collaboratively with senior Google Cloud and Google Marketing experts to apply advanced modeling techniques to enhance our customers' media/marketing solutions. As Team Lead you will be responsible for guiding the team in building out industry-relevant predictive models that can be applied to optimize our customers' media investments.

The role focuses on leading the application of analytical solutions based on machine learning & statistical predictive algorithms on top of the Google technology stack and agent development for our customers. We are looking for a Team Lead with significant experience in algorithmic data analysis, proven scientific research skills, and a track record of leading successful data science initiatives.

Skills and Experience

At WPP Media, we believe in the power of our culture and our people. It’s what elevates us to deliver exceptional experiences for both our clients and each other. In this role it will be critical to embrace WPP & WPP Media’s shared core values:

• Be Extraordinary by Leading Collectively to Inspire transformational Creativity.
• Create an Open environment by Balancing People and Client Experiences by Cultivating Trust.
• Lead Optimistically by Championing Growth and Development to Mobilize the Enterprise.

This is an excellent opportunity for a Team Lead, to join the Data and Technology Consulting Team. You will be instrumental in strategising how to tackle and take apart large and messy datasets of structured and unstructured data, oversee the building and implementation of models and algorithms, agents and design and run experiments to optimise clients customer insights, analytics and customer experience. The ideal candidate will have a love of getting their hands dirty, while also empowering and developing their team to do the same.

RESPONSIBILITIES:

• Lead the team in the creation, management, and continuous improvement of AI/ML and models and agents used to measure, optimize, and activate business transformation, including creative, media campaigns and broader marketing objectives.
• Drive the development and deployment of industry-relevant strategies and solutions.
• Ensure comprehensive documentation of data science projects, establishing best practices for replicable and scalable analytical processes across clients.
• Guide the team in building out compelling content for presentations to demonstrate the performance and value of statistical and predictive models.
• Oversee the delivery of robust mathematical analysis, ensuring accuracy and strategic relevance.
• Accountable for the team's production of high-standard campaign reports, studies, presentations, and proposals.
• Achieve continuous improvement by proactively assessing Choreograph's working relationships, practices, and methods, and implementing enhancements.
• Lead the establishment and optimization of MLOps processes leveraging the GCP toolset.
• Drive and demonstrate measurable success and impact for clients and the team.

REQUIREMENTS:

• Hands-on experience with building out machine learning models with Python, in a leadership or senior mentorship role.
• Advanced education and background in machine learning, computer science, physics, applied mathematics, or statistics.
• Expert-level hands-on experience in developing complex query structures with SQL and/or NoSQL query languages, and experience guiding others.
• Expert-level hands-on experience working with GCP’s AI Capabilities, including leveraging BigQuery ML, Vertex AI, and other relevant services.
• Extensive hands-on experience with a broad range of machine learning techniques using (TensorFlow, Keras, PyTorch, Scikit-learn, XGBoost, Pandas, NLTK, Spark MLib).
• Deep experience and understanding of deep learning techniques (TensorFlow, Theano, MXNet).
• Proven understanding and experience in software engineering best practices, DevOps, and MLOps, with a track record of implementing or leading these initiatives.
• Solid grounding in applied mathematics, especially optimization and graph theory, and advanced statistics.
• Significant commercial or academic experience in leading the development and deployment of complex ML & AI solutions using Python/R.
• In-depth knowledge of machine learning algorithms and their practical applications.
• Advantageous to have extensive experience in Google Marketing Platform and the use of Ads Data Hub.
• Exceptional capabilities in the areas of data engineering, data modeling, and complex big data analysis, with experience leading teams in these domains.
• Strong business analysis skills and deep understanding of analytics, with the ability to translate complex data into strategic business value.
• Exceptional communication and presentation skills, capable of influencing stakeholders at all levels.
• Passionate about working in an extremely fast-paced, demanding, and fluid environment, with a desire to build and lead a high-performing team and contribute significantly to a growing company.

Life at WPP Media & Benefits

Our passion for shaping the next era of media includes investing in our employees to help them do their best work, and we’re just as committed to employee growth as we are to responsible media investment. WPP Media employees can tap into the global WPP Media & WPP networks to pursue their passions, grow their networks, and learn at the cutting edge of marketing and advertising. We have a variety of employee resource groups and host frequent in-office events showcasing team wins, sharing thought leadership, and celebrating holidays and milestone events. Our benefits include competitive medical, group retirement plans, vision, and dental insurance, significant paid time off, preferential partner discounts, and employee mental health awareness days.  

WPP Media is an equal opportunity employer and considers applicants for all positions without discrimination or regard to particular characteristics. We are committed to fostering a culture of respect in which everyone feels they belong and has the same opportunities to progress in their careers.

We believe the best work happens when we're together, fostering creativity, collaboration, and connection. That's why we’ve adopted a hybrid approach, with teams in the office around four days a week. If you require accommodations or flexibility, please discuss this with the hiring team during the interview process.

Please note this is a UK based role and requires individuals to have the right to work in this location

Please read our Privacy Notice (https://www.wppmedia.com/pages/privacy-policy) for more information on how we process the information you provide.

#LI-Promoted

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

We’re looking for engineers and scientists to help accelerate our research in Artificial Intelligence as part of our mission to create the next generation of Generative AI technologies. Our team has a unique mandate: to work on speculative, longer-horizon research projects that, if successful, yield step-change improvements in the capabilities of our frontier models. We target paradigm-shifting ideas and are prepared to invest the time and resources necessary to achieve them. Our goal is to ideate, research, develop, validate, and integrate these improvements into major Google technologies.

Our primary research focus is Gemini Diffusion, our state-of-the-art text diffusion model. We believe that text diffusion has the potential to unlock a new paradigm in generative AI, offering unprecedented capabilities and lightning-fast latency. With strong backing from GDM leadership, our team is dedicated to thoroughly exploring and advancing this technology.

Our team is a multi-disciplinary group of engineers and scientists that work in close collaboration, leveraging our unique skills with a strong focus on building and shipping ground-breaking AI. We are a problem-focused team, meaning we are interested in any tool or idea that can solve a concrete problem, rather than being tied to a particular set of tools.

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

We are looking for a Research Scientist to join our team in London and help us accelerate our mission. As a Research Scientist, you will apply your deep scientific knowledge and research skills to advance paradigm-shifting research at a large scale. You will be at the heart of our efforts to deliver step-changes in the capabilities of our frontier models, with a significant focus on our Gemini Diffusion project. You will work in a tight-knit and highly collaborative team environment that fosters fundamental research and technical innovation, giving you hands-on experience with improving state-of-the-art AI systems. As a team member, your work may involve:

• Brainstorming new disruptive ideas that could become the next generation of frontier AI models, particularly within the text diffusion space.
• Prototyping and developing these ideas with the rest of the team, contributing directly to Gemini Diffusion research.
• Solving key research challenges by designing and executing experimental research on text diffusion models, sharing analyses, and proposing next steps.
• Rigorously validating the theoretical and practical impact of our work at a large scale.
• Working collaboratively with other Generative AI teams to move the technologies we develop out of the lab and into production.
• Advancing the fundamental architecture, algorithmic design, and capabilities of large-scale diffusion models.
• Bringing deep scientific expertise into our projects. You will share your insights and knowledge with other researchers and engineers. We take scientific rigor seriously, and you will be a steward of that ethos.

About you

We take a holistic view of people's backgrounds and do not expect you to be an expert in all areas. We invest heavily in training and development, and continual learning is a key part of the role. In order to set you up for success as a Research Scientist at Google DeepMind, we look for the following skills and experience:

• Advanced degree in computer science, electrical engineering, science, mathematics, or equivalent experience.
• Academic research experience in machine learning, publications, or research experience in related fields.
• Experience with some or all LLMs, Transformers, Diffusion models, Text diffusion, Large-scale distributed training.
• Strong communication skills (via discussion, presentation, technical and research writing, whiteboarding, etc.).
• Programming experience, particularly with Python-based scientific libraries such as Numpy, Scipy, JAX, PyTorch, or TensorFlow.
• Deep familiarity with the machine learning, mathematics, and statistics needed to follow relevant research papers (linear algebra, calculus, etc.) and reason about cutting-edge innovations.
• Agile and solution-focused mindset - be prepared to work on anything!

We're also interested in any of:

• A track record of building software, either in open source or as part of a company product or research papers.
• Large-scale system design, distributed systems.
• Distributed computation for ML, especially in the context of accelerators (e.g., sharding, multi-host computation).
• C++ or broader programming experience.
• Data engineering and visualisation.

At IMC, we believe technology is the foundation of our competitive edge — and machine learning is increasingly central to how we trade. Over the past few years, we've been steadily building our machine learning capabilities: developing infrastructure, growing our in-house GPU cluster, deploying models into production, and partnering closely with quant researchers and traders to generate real impact. Now we’re expanding the team, scaling our systems, and accelerating the application of deep learning in our research and execution workflows.  We're looking for a Principal Machine Learning Engineer to help shape the next phase of our platform — influencing architecture, driving best practices, and solving high-leverage problems. You’ll work alongside researchers and technologists to design the systems that power experimentation, training, and deployment of ML models — and help set the direction for how machine learning is done at IMC as we scale. If you’ve built ML infrastructure at scale elsewhere and are looking for a role where your ideas will genuinely help shape our firm’s future — we’d love to hear from you.

Your Core Responsibilities: 

• Design and build end-to-end infrastructure for training, evaluation, and productionization of ML models, working closely with our HPC engineers who manage our on-prem compute cluster
• Influence foundational choices around data access, compute orchestration, experiment tracking, model versioning, and deployment pipelines
• Partner with quant researchers to accelerate iteration cycles, tighten feedback loops, and bring models from prototype to live trading
• Work with researchers to adapt and deploy modern architectures — transformers, state-space models, temporal convolutions, graph neural networks — to noisy, high-frequency financial data. Explore techniques like self-supervised pretraining, representation learning, and cross-sectional modelling where they offer genuine edge
• Shape our approach to reproducibility, continual learning, and production monitoring across a petabyte-scale data environment
• Define standards that create consistency across teams and geographies; mentor engineers and influence technical culture beyond your immediate work
• Keep pace with developments in deep learning research and ML infrastructure; bring ideas from academia and industry into how we work — whether that's new architectures, training techniques, or tooling

Your Skills and Experience: 

• 8+ years of experience building ML platforms or infrastructure at a leading tech company, research lab, or quantitative firm
• A track record of designing and owning large-scale training and inference systems — not just contributing, but architecting
• Deep proficiency in Python, with strong experience in either CUDA or C++
• Hands-on expertise with modern deep learning frameworks (PyTorch, TensorFlow, or JAX) and practical experience implementing architectures like transformers, attention mechanisms, or sequence models
• Strong foundation in deep learning fundamentals: optimization, regularization, loss design, and the trade-offs that matter when training at scale
• Experience with distributed training at scale (Horovod, NCCL) and GPU optimization (cuDNN, TensorRT)
• History of deploying models to production with strong observability, reproducibility, and monitoring practices
• Comfort working across the ML stack from data pipelines to training infrastructure to serving systems

Why This Role: 

• Build, don't inherit — You'll make foundational technology choices in a platform that's still being defined, not maintain someone else's legacy.
• Real investment, real backing — This is a strategic priority with resources behind it, not a side experiment.
• Direct impact on trading — Your infrastructure will power models that make real trading decisions in competitive global markets.
• Global scope — Work with teams across New York, Chicago, Amsterdam, London, Sydney, Hong Kong and beyond; define practices that can scale worldwide.
• Ideas over titles — IMC's culture values clarity, rigor, and collaboration. The best ideas win, regardless of where they come from.
• Tight coupling with research — You won't be building in isolation. Researchers and engineers work side-by-side, iterating together.

#LI-DNP

As a Machine Learning Engineer, you will play a pivotal role in building systems that drive the training and deployment of large-scale ML models across our global operations. You'll collaborate with leading researchers, hardware experts, and software engineers to build robust solutions that maximize the potential of GPU acceleration, distributed computing, and the latest open-source tools. Your work will influence our trading strategies by accelerating experimentation cycles that foster continuous innovation and refinement.

This is a unique opportunity to solve problems at the intersection of advanced machine learning and trading, where your contributions will shape the future of IMC’s technology and trading capabilities.

Your Core Responsibilities: 

• Develop large-scale distributed training pipelines to manage datasets and complex models
• Build and optimize low-latency inference pipelines, ensuring models deliver real-time predictions in production systems
• Develop libraries to improve the performance of machine learning frameworks
• Maximize performance in training and inference using GPU hardware and acceleration libraries
• Design scalable model frameworks capable of handling high-volume trading data and delivering real-time, high-accuracy predictions
• Collaborate with quantitative researchers to automate ML experiments, hyperparameter tuning, and model retraining
• Partner with HPC specialists to optimize workflows, improve training speed, and reduce costs
• Evaluate and roll out third-party tools to enhance model development, training, and inference capabilities
• Dig into the internals of open-source ML tools to extend their capabilities and improve performance

Your Skills and Experience: 

• 5+ years of experience in machine learning with a focus on training or inference systems
• Hands-on experience with real-time, low-latency ML pipelines in high-performance environments is a strong plus
• Strong engineering skills, including Python, CUDA, or C++
• Knowledge of machine learning frameworks such as PyTorch, TensorFlow, or JAX
• Proficiency in GPU programming for training and inference acceleration (e.g., CuDNN, TensorRT)
• Experience with distributed training for scaling ML workloads (e.g., Horovod, NCCL)
• Exposure to cloud platforms and orchestration tools
• A track record of contributing to open-source projects in machine learning, data science, or distributed systems is a plus

#LI-DNP