machine learning lead

Alignerr

<div>
 
 About The Role
 
 
 
 What if your machine learning expertise could directly influence how the most advanced AI systems in the world think, reason, and write code? We're looking for experienced ML engineers in London to evaluate AI-generated machine learning solutions &mdash; catching errors, improving quality, and helping frontier AI models get genuinely better at one of the hardest things they do.
 
 
 This is a fully remote, flexible contract role. Work asynchronously on your own schedule, from wherever you are. No fixed hours, no meetings &mdash; just high-impact, expert work that matters.
 
 
 <ul>
 <li>
 Organization: Alignerr
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 Type: Hourly Contract
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 Location: Remote (UK-based)
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 Commitment: Flexible, project-based
 
 
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 </ul>
 
 What You'll Do
 
 
 
 <ul>
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 Review and evaluate AI-generated machine learning code &mdash; including Python, TensorFlow, PyTorch, and scikit-learn &mdash; for correctness, efficiency, scalability, and clarity
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 Write high-quality ML solutions to modeling, data processing, and deployment problems across a range of difficulty levels
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 Craft clear, developer-friendly explanations for model architecture decisions, code logic, and problem-solving approaches
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 Identify edge cases, ambiguities, and weaknesses in problem statements, datasets, or AI-generated responses
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 <li>
 Help set the quality bar for how AI understands and produces machine learning code
 
 
 </li>
 </ul>
 
 Who You Are
 
 
 
 <ul>
 <li>
 Deeply fluent in machine learning &mdash; you know your way around model development, data preprocessing, training pipelines, and deployment
 </li>
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 Hands-on experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn
 </li>
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 Strong written communicator &mdash; able to explain complex ML concepts clearly and precisely
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 Detail-oriented and rigorous &mdash; you catch what others miss and care about getting things right
 </li>
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 Self-motivated and comfortable working independently in an async environment
 
 
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 </ul>
 
 Nice to Have
 
 
 
 <ul>
 <li>
 3&ndash;5+ years working on machine learning projects, pipelines, or MLOps
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 Experience with model evaluation, cloud deployment, or production ML systems
 </li>
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 Bachelor's, Master's, or PhD in Computer Science, Machine Learning, or a related field
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 Background in data labeling, RLHF, or other AI training workflows
 </li>
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 Prior experience with code review or technical writing
 
 
 </li>
 </ul>
 
 Why Join Us
 
 
 
 <ul>
 <li>
 Work on cutting-edge AI projects alongside leading research labs and top AI teams
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 Fully remote and async &mdash; work when and where it suits you, with no minimum hour commitments beyond project needs
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 Freelance autonomy with the structure of meaningful, task-based work
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 Your contributions directly improve AI models used by top research labs and enterprise teams worldwide
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 High-performing contributors take on expanded responsibilities and lead new programs
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 Potential for ongoing work and contract extension as new projects launch
 </li>
 </ul>
</div>

Software Engineer – Machine Learning (AI Training)

Talan

<div>Company Description 
Talan Data x AI is a leading Data Management and Analytics consultancy, working closely with leading software vendors and top industry experts across a range of sectors, unlocking value and insight from their data. At Talan Data x AI, innovation is at the heart of our client offerings, and we help companies to further improve their efficiency with modern processes and technologies, such as Machine Learning (ML) and Artificial Intelligence (AI). 
Job Description 
We are hiring a Lead Data Scientist to drive the technical delivery of our most demanding AI engagements and to lead a growing team of data scientists and AI engineers. This role is for a practitioner who is equally fluent in the rigour of traditional data science (statistical modelling, machine learning, experimentation) and the fast-moving world of large language models and agentic AI. You understand that the best solutions often combine both.
You will own delivery from problem framing through to deployment, ensuring the work is technically sound, commercially valuable, and aligned to the architectural vision. As a lead, you will mentor the team, raise engineering and modelling standards, and act as a trusted technical partner in client conversations. You will help clients see not just what is possible, but what is practical and worth doing.
This is a delivery-focused leadership role with genuine breadth: one week you might be tuning a forecasting model, the next designing an agentic workflow or evaluating an LLM pipeline for a client pilot.
Required skills &amp; experience:<ul><li>
Lead end-to-end delivery of data science and AI projects, owning technical quality and outcomes.</li><li>
Combine classical ML (regression, classification, forecasting, optimisation) with modern GenAI, LLM, and agent-based approaches as the problem demands.</li><li>
Mentor and develop data scientists, AI engineers, and junior consultants, growing the team's capability.</li><li>
Translate business problems into well-scoped analytical and AI solutions and communicate results to non-technical stakeholders.</li><li>
Ensure best practice across the AI lifecycle &mdash; experimentation, evaluation, testing, deployment, and monitoring.</li><li>
Act as the bridge between architecture and delivery, ensuring implementation stays faithful to design.</li><li>
Support pre-sales and client discussions with credible technical input and realistic estimation.</li><li>
Champion reproducibility, model governance, and responsible practice in everyday delivery.</li></ul> 

Qualifications 
To qualify for this role, you must have:
<ul><li>Minimum 5 years in data science or AI delivery, including hands-on leadership of technical teams or workstreams.</li><li>
Strong foundations in machine learning and statistics, with demonstrable production experience.</li><li>
Practical experience with LLMs and generative AI &mdash; prompting, RAG, fine-tuning, and evaluation.</li><li>
Exposure to AI agents and orchestration frameworks, and an appetite to deepen it.</li><li>
Proficiency in Python and the modern data / ML stack; sound data engineering instincts.</li><li>
Excellent communication and stakeholder skills, ideally in client-facing or consulting settings.</li></ul>
Ideally, you&rsquo;ll also have, but not essential:<ul><li>
Familiarity with the Azure AI ecosystem (Azure ML, Azure OpenAI, Databricks / Fabric).</li><li>
Experience supporting business development or pre-sales.</li><li>
Domain depth in a regulated or data-rich industry.</li><li>
Contributions to open source, publications, or a visible professional profile.</li></ul>
You must be:<ul><li>
Willing to work on client sites, potentially for extended periods.</li><li>
Willing to travel for work purposes and be happy to stay away from home for extended periods.</li><li>
Eligible to work in the UK without restriction.</li></ul>
#TalanUK #LI-HB1 
Additional Information 
Compensation &amp; Benefits Package:<ul><li>
BDP Plus &ndash; A reward programme whereby you accrue points to trade against a 3-month paid sabbatical or cash equivalent.</li><li>
25 days holiday + bank holidays.</li><li>
5 days holiday buy/sell option.</li><li>
Private medical insurance.</li><li>
Life cover.</li><li>
Cycle to work scheme.</li><li>
Eligibility for company pension scheme (5% employer contribution, salary sacrifice option).</li><li>
Employee assistance programme.</li><li>
Bespoke online learning via Udemy for Business.</li></ul>
Why join:
You will lead substantive, end-to-end AI work in a practice that is scaling fast and backing its people to grow with it. You will shape how a team works, influence how clients adopt AI, and keep your own skills at the frontier, bridging proven data science with the most current GenAI and agentic techniques. It is an opportunity to lead, deliver, and keep building.</div>

Lead Data Scientist (Classical ML, LLMs & AI Agents)

Amazon.com

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
Amazon Strategic Account Services (SAS) Tech Organization is looking for an Applied Scientist Applied Scientist who can autonomously drive scientific innovations from research to production, developing sophisticated AI solutions that serve both Amazon's global seller base and internal Marketplace Consultants. Working in a highly collaborative environment, you'll leverage expertise in machine learning, operations research, and statistics to translate theoretical advances in LLMs, probabilistic modeling, and optimization into practical applications. The role demands strong capabilities in prototyping and iterative improvement, bridging cutting models with real-world applications while maintaining scientific rigor and measurable business impact. 
 
Key job responsibilities 
<ul><li>Lead the development of sophisticated AI solutions leveraging deep learning, LLMs, and advanced machine learning techniques to transform both seller operations and internal consultancy capabilities at scale</li><li>Define and drive long-term scientific vision for the organization, translating complex business challenges into innovative technical solutions that advance the state-of-the-art in applied machine learning</li></ul>
- Design and implement advanced ML architectures combining multiple learning paradigms - from reinforcement learning and causal inference to predictive modeling - to tackle critical marketplace challenges 
<ul><li>Architect next-generation recommendation and optimization systems that handle complex multi-dimensional constraints while maintaining robustness and interpretability at scale</li><li>Drive end-to-end development of AI applications from research through production, collaborating with engineering teams to ensure successful deployment and conducting rigorous A/B experiments to validate impact</li><li>Pioneer novel applications of foundation models and generative AI, developing sophisticated evaluation frameworks while maintaining Amazon's high standards for accuracy and reliability</li><li>Lead technical discussions across organizational boundaries, effectively communicating complex scientific concepts to diverse stakeholders while staying at the forefront of ML/AI research advancements</li></ul> 
About the team 
What is Amazon Strategic Account Services (SAS)? 
The SAS team aims to accelerate the full potential of our Sellers, helping them to navigate the increasing complexity of the e-commerce space. Our team provides in-depth strategic consultancy using a data-driven, collaborative, and a Customer-focused approach to achieve commercial goals of Amazon Sellers.
</div><h2 class="jobSectionHeader">BASIC QUALIFICATIONS</h2><ul><li>PhD, or a Master's degree and experience in building models for business application</li><li>Experience programming with at least one modern language such as Java, C++, or C# including object-oriented design</li><li>Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Track record of investigating, designing, and delivering innovative ML solutions that drive significant business impact</li></ul> 
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates. 
 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner.</div>

Applied Scientist II, Strategic Account Services (SAS)

Hiscox

<div>
 
 Job Type
 
 
 
 Permanent
 
 
 
 Build a brilliant future with Hiscox
 
 
 
 
 Reporting to: Re &amp; ILS Head of Data
 
 
 
 
 Location:
 
 London
 
 
 Type: Permanent
 
 
 
 Role Overview
 
 
 
 The Lead Data Scientist is a crucial member of the
 
 extended
 
 RE&amp;ILS Tech Leadership Team, responsible for building, leading, and nurturing a highly capable (New)
 
 Data Science and Machine Learning
 
 chapter.
 
 
 This role facilitates the successful delivery of new AI Cloud-based solutions against our growing list of business use cases (involving complex Data Analytics, Machine Learning, and AI Agent based solutions).
 
 
 You will co-lead the new Data Science chapter with the RE&amp;ILS Head of Data and help ensure its members provide Data Science capabilities and insights to support decision-making across RE&amp;ILS strategic Value Streams. Whilst the chapter grows, you are expected to be
 
 hands-on
 
 actively helping to architect, design, and build AI or Data Science-based solutions, using internally trained models, LLMs and/or a combination of both.
 
 
 Whilst undertaking this pioneering work it is essential that you and your entire chapter operates within the boundaries of the
 
 Group AI Governance Framework
 
 and maintains rigorous data governance standards. You will be accountable of this adherence.
 
 
 This is likely to be your first managerial role and the first time you have had one or more direct reports &ndash; having previously been a Senior Data Scientist or Machine Learning Engineer yourself. In this role you will be responsible for the management of a 1 to 4 junior and mid-level Hiscox FTEs and Partner resources too. You will be expected to support the Head of Data with attracting and retaining the best talent; helping to manage their career progression and ensure they are highly engaged, find the work fulfilling, and have the ability to rapidly deliver value to the business. As this is likely to be your first managerial role you will be supported and guided by other Data Leaders &ndash; Head of Data and the Hiscox Group Head of Data Science as well.
 
 
 
 About Hiscox Re &amp; ILS
 
 
 
 Hiscox Re &amp; ILS is located in
 
 Bermuda and London
 
 and underwrites reinsurance risks from around the world on behalf of our own and other people&rsquo;s capital. The team of over 100 smart, enthusiastic individuals are committed to providing top quality service to brokers and clients across a broad range of reinsurance products. Our approach is simple; match the best underwriting risk against globally diversified capital. Our proactive, product-led underwriting approach is complemented by a commitment to world class service and purpose-built analytics and systems. We know our people are our biggest asset so finding and retaining the best talent is critical to achieving our vision.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Chapter Leadership &amp; Talent Management
 </li>
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 People Management: Lead, recruit, mentor, coach, train, and retain a high-performing chapter of Data Scientists and Machine Learning Engineers (expected to grow to over the next few years), including both Hiscox FTE and Partner colleagues. Inspire chapter members to be curious, embrace new ideas, and nurture psychological safety to help build a high-performance culture.
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 In this role you will manage at least one to two Hiscox data scientists and some partner resources too. You will be expected to manage their performance with relevant PDRs and help to calibrate their overall performance ratings with other people managers in the team. You will work with the Head of Data and Group Head of Data Science to help tailor the training needs to suit each individual and ensure they have the opportunity to grow and progress in their chosen career paths.
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 Culture &amp; Development: Cultivate a collaborative, engaged, and fulfilled team culture. Provide technical leadership, career guidance, and direction to the team, ensuring successful delegation to all chapter members.
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 Best Practice: Ensure the chapter adheres to best practices in data science, AI, and complex analytics, sharing knowledge across the wider Hiscox Analytics and Data community through active participation in Communities of Practice.
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 Mentoring: Mentor and educate others in the various data science techniques, encouraging the team to continually learn &ndash; especially supporting the adoption of LLMs and proprietary models that could significantly accelerate our ability to deploy value.
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 Solution Delivery &amp; ML Ops Excellence
 </li>
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 Hands-On Architecture: Get hands-on to help architect, design, and build complex models that integrate into existing IT solutions to improve data-driven decision-making throughout the Reinsurance Value Chain. Ensure you and your chapter members work closely with Platform Engineers and Architects to create the most optimal and safe solutions.
 </li>
 <li>
 ML Ops Platform: Actively work with the Head of Platform Engineering to establish and maintain a professional ML Ops platform to facilitate the effective support of developed models in production. This includes embedding a rigorous model evaluation process, ensuring consistent model refresh/rebuild capabilities due to model or data drift, and implementing effective monitoring and alerts against rogue behaviour.
 </li>
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 Speed of Execution: Empower the chapter to work effectively within autonomous squads, delivering desired and valuable outcomes in an incremental manner while correctly balancing accuracy, fast return on investment, and reliability. Understand when to move on and fail fast &ndash; as a lot of AI use cases will be highly experimental in nature with no guarantees of success.
 </li>
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 Pipeline Collaboration: Work with Data Engineering and other teams to properly understand and contribute to the requirements and building of necessary data pipelines/products consumed by our models.
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 Strategy, Governance &amp; Innovation
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 Use Case Identification: Continually work with key business leaders, the Head of Data and key stakeholders to identify new use cases and opportunities where data science/AI can deliver a competitive advantage or reduce waste/costs through efficiency gains.
 </li>
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 Governance &amp; Compliance: Champion data and model governance, working within the Group AI Governance Framework. Ensure a mature understanding of data governance, lineage, and version control, and enforce data privacy by design in all new work.
 </li>
 <li>
 Innovation: Maintain a strong awareness of new trends and techniques in Data Science, AI, and Machine Learning. Drive the identification of innovative data solutions and technologies, and actively undertake Proof of Concepts and R&amp;D to deliver reliable insights and potential next steps quickly.
 </li>
 <li>
 Communication: Ensure clear and effective communication of data science solutions and outcomes across business layers, technical teams, and senior leadership.
 
 
 
 </li>
 </ul>
 
 Required Experience And Structure
 
 
 
 <ul>
 <li>
 Reporting: Reports into the RE&amp;ILS Head of Data with a dotted line into the new Group Head of Data Science.
 </li>
 <li>
 Direct Reports: Direct line management for Data Scientists and Machine Learning Engineers within the RE&amp;ILS Data Science Chapter.
 </li>
 <li>
 Key Partners: RE&amp;ILS CTO, Group Head of Data Science, RE&amp;ILS Head of Data, Product Managers, Product Owners, and strategic partners (e.g. Google Cloud, Microsoft).
 
 
 
 </li>
 </ul>
 
 Candidate Profile
 
 
 
 The successful candidate will be an energetic, highly capable, and passionate Senior Data Scientist who wants to move into their first people management role. You will need to balance technical expertise with effective people management and strategic business partnership. You must be comfortable working in an FCA-regulated business, advocating for a data-driven approach, and driving innovation while maintaining rigorous AI governance standards. You will have a strong determination and resilience and not fear failure or the inevitable setbacks often found in highly experimental work.
 
 
 
 Main Experience Required Is
 
 
 
 <ul>
 <li>
 Deep Interest in Leadership: As an experienced data scientist or machine learning engineer, has previously demonstrated excellent traits in mentoring and coaching more junior team members and has been happy to invest in them - clearly demonstrating they care about other peoples&rsquo; career progression. Also you can evidence some successful business outcomes that you personally drove forward using advanced Data Science/AI &ndash; as this most likely is your first leadership role.
 </li>
 <li>
 Technical Depth: Extensive "hands-on" experience in architecting, designing, and building complex ML models, with a strong understanding of cloud services and the AI/ML/LLM ecosystem.
 </li>
 <li>
 ML Ops Maturity: Proven ability to build, maintain, and support production-deployed models, including establishing effective monitoring, evaluation, and refresh processes.
 </li>
 <li>
 AI and Data Governance: Mature understanding of AI and Data governance - data obfuscation &amp; data privacy laws, data version control, data lineage, and the application of AI governance frameworks in a regulated environment.
 </li>
 <li>
 Stakeholder Management: Experience in managing and driving collaboration with business unit leaders (Underwriters, pricing teams, MI team) and external technology partners like Google Cloud, Snowflake, DataIku and Microsoft.
 </li>
 <li>
 Education: Bachelor's/Master's degree in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Physics, Engineering) or equivalent.
 </li>
 <li>
 Capacity for independent, high-quality research and exploratory data analysis, with the ability to develop and apply novel methodologies to solve ill-defined and challenging business problems.
 </li>
 <li>
 Exceptional proficiency in Python (and R) for data science, coupled with SQL capabilities for data manipulation and extraction. Demonstrable mastery in a wide range of machine learning and statistical modelling techniques, from classical linear models and tree-based methods to advanced deep learning architectures.
 </li>
 <li>
 Real world experience with, or demonstrable capability for, applications of Generative AI, Large Language Models (LLMs), AI Agents and related areas such as Natural Language Processing (NLP) or Computer Vision, relevant to business solutions.
 </li>
 <li>
 Demonstrate a Solid understanding of foundational statistics and experimental design. Pioneer the development and robust deployment of highly impactful machine learning and AI-driven solutions, directly contributing to significant commercial value, quantifiable business growth, or efficiency gains across the organization.
 </li>
 <li>
 Ability to translate complex data science insights into tangible, measurable improvements across critical business processes and key performance indicators, ensuring the real-world adoption and beneficial outcomes of our analytical work.
 </li>
 <li>
 Ability to elevate the technical maturity and capabilities of the data science chapter by shaping and implementing industry-leading AI, data, and analytics techniques, methodologies, and engineering best practices.
 </li>
 <li>
 Educator: shown the ability to train and coach more junior and mid-level team members - ensuring they have excellent career progression and become high performers.
 
 
 
 </li>
 </ul>
 If you are a visionary expert looking for your first leadership role and ready to accelerate our value delivery and champion all things Data Science and AI, we invite you to apply for the position of Lead Data Scientist at Hiscox Re &amp; ILS. Join our team and be a catalyst for AI adoption in a dynamic, forward-thinking organization.
 
 
 
 Work with amazing people and be part of a unique culture
 
</div>

Lead Data Scientist

<div>Company Description 
Talan Data x AI is a leading Data Management and Analytics consultancy, working closely with leading software vendors and top industry experts across a range of sectors, unlocking value and insight from their data. At Talan Data x AI, innovation is at the heart of our client offerings, and we help companies to further improve their efficiency with modern processes and technologies, such as Machine Learning (ML) and Artificial Intelligence (AI). 
Job Description 
As our AI practice grows, we are looking for a capable, hands-on AI Engineer to help build and deliver the solutions at the heart of our client work. Coming from a data science background, you are equally comfortable applying proven machine-learning techniques to traditional analytics problems and working with the latest generative AI (large language models, retrieval-augmented generation, and agent-based applications). You enjoy building, you write dependable code, and you turn well-defined designs into working software.
This is a delivery-focused role that sits a level below our Lead Data Scientists. You will own meaningful workstreams within a project rather than the whole engagement, working to an architecture and plan shaped by more senior colleagues. In return, you will gain breadth across modern AI, exposure to real client problems,
You will also be a supportive presence within the team, helping your peers solve problems, sharing what you learn, and giving day-to-day guidance to graduate and junior resources working alongside you.
Required skills &amp; experience:<ul><li>
Build, test, and deploy AI and machine learning components within client projects to the standards and designs set by senior colleagues.</li><li>
Develop GenAI and LLM-based features (prompting, retrieval-augmented generation, and simple agentic workflows) alongside more traditional ML models.</li><li>
Deliver classical data science tasks (data preparation, feature engineering, model training, and evaluation) on projects that call for them.</li><li>
Translate solution designs into clean, well-documented, production-minded code.</li><li>
Contribute to model evaluation, testing, and monitoring.</li><li>
Support and guide very junior and graduate resources, reviewing their work and helping them grow.</li><li>
Help peers unblock technical problems and share knowledge across the team.</li><li>
Take part in client and team discussions and communicate your work clearly.</li></ul> 

Qualifications 
To qualify for this role, you must have:
<ul><li>Typically, 2&ndash;4 years' experience in data science, machine learning, or AI engineering.</li><li>
Solid grounding in core data science and machine learning.</li><li>
Practical experience with LLMs and generative AI, including prompting and RAG.</li><li>
Familiarity with how AI agents are built and orchestrated.</li><li>
Strong Python and common data/ML libraries; good engineering habits.</li><li>
Clear communicator and collaborative team player.</li></ul>
Ideally, you&rsquo;ll also have, but not essential:<ul><li>
Exposure to cloud AI platforms, Azure a plus.</li><li>
Experience practicing MLOps and LLMOps.</li><li>
Early experience mentoring junior colleagues.</li><li>
Interest in consulting and client-facing delivery.</li></ul>
You must be:<ul><li>
Willing to work on client sites, potentially for extended periods.</li><li>
Willing to travel for work purposes and be happy to stay away from home for extended periods.</li><li>
Eligible to work in the UK without restriction.</li></ul>
#TalanUK #LI-HB1 
Additional Information 
Compensation &amp; Benefits Package:<ul><li>
BDP Plus &ndash; A reward programme whereby you accrue points to trade against a 3-month paid sabbatical or cash equivalent.</li><li>
25 days holiday + bank holidays.</li><li>
5 days holiday buy/sell option.</li><li>
Private medical insurance.</li><li>
Life cover.</li><li>
Cycle to work scheme.</li><li>
Eligibility for company pension scheme (5% employer contribution, salary sacrifice option).</li><li>
Employee assistance programme.</li><li>
Bespoke online learning via Udemy for Business.</li></ul>
Why join:
This is a role built for momentum, working across the full spectrum of modern AI, learning from senior architects and leads on real engagements, with genuine responsibility from day one and a clear path into a leadership track.</div>

AI Engineer (LLMs, Agents & Applied Data Science)

PROXIMIE

<div>Proximie is on a mission to improve healthcare by transforming the world&rsquo;s operating rooms into connected ecosystems of people, devices, and data.<div>
Our Intelligence Suite transforms operating room (OR) performance, keeping teams in sync and workflows on track to maximise throughput. Simultaneously our computer vision and AI capabilities capture real-time data and detect surgical events &ndash; improving quality of data outputs. The result: ORs are optimised like never before &ndash; with predictive analytics and automated notifications ensuring patients and staff are in the right place at the right time.
Once practitioners are in the OR, our Surgical Suite enables real-time remote access and creates a secure video record of every procedure; improving training, education, and collaboration. It is an intuitive asset which helps instil a culture of continuous learning, accelerates the adoption of cutting-edge medical devices, and enhances surgical performance across the entire global workforce &ndash; improving outcomes and saving lives.
Proximie was commercialised in 2019 and is available in over 500 facilities globally.
Check out our Founder and CEO Nadine&rsquo;s Origins Story here: https://www.proximie.com/about-us/
Position Overview
As Proximie continues to turn every activity and event in the operating room into comprehensive, structured, and context-rich data that drives better insights and decisions making, using your deep technical expertise and real-world experience you will be instrumental in developing and deploying machine learning solutions that improve clinical outcomes, drive productivity and support Proximie&rsquo;s continuing evolution into the unrivalled champion of the intelligent operating room.
You will work with multi-modal data (audio, vision, and language) to curate, consolidate, and augment retrospective and prospective datasets that fuel the development of advanced machine learning solutions. You&rsquo;ll harness the power of Proximie&rsquo;s deep data lakes and apply cutting-edge generative techniques to solve real-world challenges for Proximie&rsquo;s customers. You&rsquo;ll also lead the development of intelligent systems that can automatically detect and capture key events in the operating room, designing robust solutions that work across diverse and unpredictable data distributions, tackling challenges like identifying rare events buried in hours of surgical video.
This role demands creativity, precision, and a deep understanding of real-world machine learning at scale. If you&rsquo;re excited by complex problems with life-changing impact and want to build tech that operates in the most critical environments, we&rsquo;d love to hear from you.
Responsibilities<ul><li>
Collaborate with product, engineering and commercial teams to develop and deploy AI models for real world application in hospitals all over the world.</li><li>
Design, train and validate machine learning mono and multi-modal models using state of the art approaches.</li><li>
Develop models and derived tools robust to the heterogeneity of operating room environments. With customers all over the world operating rooms are often different which creates unique opportunities for problem solving and model design.</li><li>
Own the full model lifecycle including but not limited to data curation, model implementation, training, validation, deployment, and maintenance.</li><li>
Development within Proximie environment to enable dynamic model training and performance evaluation while integrating with Proximie&rsquo;s data lakes.</li><li>
Document solutions and contribute to internal knowledge sharing and capability building.</li></ul><div>
Requirements<ul><li>
PhD in a machine learning field such as computer science, data science, engineering, or a related field. Masters considered but PhD preferred.</li><li>
Minimum of 4 years&rsquo; hands-on experience in industry, developing and deploying AI solutions which solve real-world problems.</li><li>
Expertise in developing, training and fine-tuning machine learning and multi-modal models. Experience in training models with data originating from heterogeneous distributions is highly desirable.</li><li>
Deep knowledge of a variety of traditional machine learning, deep learning and generative AI methods for both supervised, self-supervised and unsupervised learning with an emphasis on vision.</li><li>
Proficiency with deep learning frameworks such as TensorFlow/PyTorch.</li><li>
Proficiency with Python and strong software development background.</li><li>
Knowledge and experience with AWS is highly desirable.</li><li>
Experience with MLOps practices, including versioning, deployment, and monitoring of models highly desirable.</li><li>
Ability to communicate complex technical concepts clearly to non-technical stakeholders.</li></ul>
Why Work for Proximie?<ul><li>
You will be encouraged to grow in your role, take ownership and gain responsibilities. Proximie&rsquo;s values are Ownership, Deliver Results, Build Trust and Go Beyond.</li><li>
Generous annual leave.</li><li>
Two &ldquo;well-being&rdquo; days per year plus the day off for your birthday.</li><li>
&ldquo;Summer Fridays&rdquo; &ndash; early office closing on Fridays during summer months.</li><li>
Annual bonus programme &ndash; based on individual contribution.</li><li>
To support your professional growth, all permanent employees will have access to an annual stipend of &pound;1,000 to assist with personal development activities.</li><li>
Flexible working hours - we trust our people to manage their time and to focus on wider results.</li><li>
A flat organizational structure where every opinion matters, ideas are cultivated, and innovation is encouraged.</li><li>
Proximie is a truly global company with teams across the UK, Europe, United States and the Middle East with that you will have opportunities to see the world.</li></ul>
Proximie is an equal opportunity employer. We are committed to providing a work environment that supports, inspires, and respects all individuals. We do not discriminate on the basis of race, colour, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under the law.</div></div></div>

Senior Machine Learning Engineer

Data Idols

<div><h2 class="jobSectionHeader">Senior Data Scientist</h2>
<h3 class="jobSectionHeader">Salary: &pound;85K &ndash; &pound;95K</h3>
<h3 class="jobSectionHeader">Location: London (Hybrid &ndash; 3 days per week)</h3>

Data Idols are working with an ambitious early-stage technology company that is building a machine learning platform capable of solving complex behavioural prediction problems at scale.

Already working with paying customers and backed by experienced founders with a successful track record of building and exiting technology businesses, they&rsquo;re now looking for a Senior Data Scientist to own one of the most important parts of the company.
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The Opportunity</h3>

This isn&rsquo;t a role where you&rsquo;ll optimise an existing model or become another specialist in a large data science team.

You&rsquo;ll be responsible for designing and building the machine learning capability at the heart of the business. Rather than creating a single predictive model, you&rsquo;ll develop automated systems capable of generating, deploying and continuously improving bespoke machine learning models for every customer.

You&rsquo;ll work with large-scale behavioural event data, applying machine learning, feature engineering and experimentation to improve prediction accuracy and drive measurable customer outcomes.

Working alongside highly experienced founders and recognised experts in machine learning, you&rsquo;ll have the opportunity to influence product strategy, shape technical direction and establish best practices from day one.

This is a genuine ownership role where your work will have a direct impact on both the product and the future success of the business.
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Skills &amp; Experience</h3>
<ul><li>Strong commercial experience building machine learning models in Python</li>
<li>Excellent understanding of predictive modelling, classification or propensity modelling</li>
<li>Experience with feature engineering, model evaluation and experimentation</li>
<li>Comfortable working across the full machine learning lifecycle</li>
<li>Experience working with cloud platforms and modern ML tooling</li>
<li>Curious and analytical mindset</li>
</ul>
If you&rsquo;re looking for a role where you&rsquo;ll solve genuinely difficult machine learning challenges, build something from the ground up and see the direct impact of your work, we&rsquo;d love to hear from you.
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Senior Data Scientist</h2></div><div></div>

Senior Data Scientist

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