data engineer

data scientist

machine learning engineer

senior data scientist

senior ai engineer

machine learning researcher

Data Idols

<div><h2 class="jobSectionHeader"><b>Senior Data Scientist</b></h2>
<h3 class="jobSectionHeader"><b>Salary: &pound;85K &ndash; &pound;95K</b></h3>
<h3 class="jobSectionHeader"><b>Location:</b><b> London (Hybrid &ndash; 3 days per week)</b></h3>
<p>
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.</p>
<p>
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.</p>
<h3 class="jobSectionHeader"><b>
The Opportunity</b></h3>
<p>
This isn&rsquo;t a role where you&rsquo;ll optimise an existing model or become another specialist in a large data science team.</p>
<p>
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.</p>
<p>
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.</p>
<p>
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.</p>
<p>
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.</p>
<h3 class="jobSectionHeader"><b>
Skills &amp; Experience</b></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>
<p>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.</p>
<h2 class="jobSectionHeader"><b>
Senior Data Scientist</b></h2></div><div></div>

Senior Data Scientist

Alignerr

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


Software Engineer – Machine Learning (AI Training)

HOMETRACK

<div><p>Hometrack is redefining the mortgage journey for lenders, brokers, and consumers by delivering market-leading valuation and property data services to the financial, property, and technology industries. Our key commercial and go-to-market segment is in financial services, primarily mortgage lenders, including nine of the top 10 mortgage providers.</p><p>
At Hometrack, we are looking for an experienced Senior Machine Learning Engineer, to translate POC model code from data science and analytics into robust pipelines and live APIs.</p><p></p><p>
Responsibilities:</p><ul><li>
Oversee the deployment of machine learning models into production, ensuring they perform well in real-world conditions and monitoring their performance over time.</li><li>
Work closely with data scientists, software engineers, product managers, and stakeholders to integrate machine learning solutions into our products and services.</li><li>
Develop automated workflows for model retraining, testing, and deployment to streamline the machine learning lifecycle.</li><li>
Advocate for and implement best practices in software engineering, including code reviews, continuous integration, and continuous delivery (CI/CD) for machine learning models.</li></ul><p></p><p>
Requirements:</p><ul><li>
Strong understanding of machine learning applications, development life cycle processes and tools: CI/CD, version control, testing frameworks, MLOps.</li><li>
Strong Python experience and knowledge, with the ability to write stable, scalable and maintainable code.</li><li>
Experience with data science Python libraries such as Sckit-learn, Pandas, NumPy, PyTorch, PySpark, LightGBM.</li><li>
Have worked with a cloud service, such as AWS.</li><li>
Familiarity developing Infrastructure as code (e.g Terraform, cloudformation).</li><li>
Have some experience with data engineering, building data pipelines with PySpark, SQL (E.g in Databricks, Glue) to power machine learning applications.</li><li>
Comfortable working with Docker and containerised applications.</li><li>
Experience leveraging AI native engineering tooling.</li><li>
Passion for building products that meet customer needs and business objectives.</li><li>
Strong sense of responsibility and a track record of delivering high-quality results in a fast-paced environment.</li></ul><br>
<b>
Benefits</b><br>
<ul><li>
Everyday Flex - greater flexibility over where and when you work</li><li>
25 days annual leave + extra days for years of service</li><li>
Day off for your birthday, house move, good deed day, and digital detox day</li><li>
Cycle to work and electric car schemes
</li><li>Free Calm App membership
</li><li>Enhanced Paternity Leave
</li><li>Fertility Treatment Financial Support
</li><li>Group Income Protection and private medical insurance</li><li>
Gym on-site in London &ndash; or membership in regional offices</li><li>
7.5% pension contribution by the company</li><li>
Discretionary annual bonus up to 10% of base salary</li><li>
Talent referral bonus up to &pound;5K</li></ul></div>

Senior Machine Learning Engineer

JPMorganChase

<div><b>JOB DESCRIPTION</b><br>
<br>
<br>
<div></div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><div><p>The Chief Data &amp; Analytics Office (CDAO) at JPMorgan Chase is responsible for accelerating the firm's data and analytics journey. As a part of CDAO, The Machine Learning Center of Excellence (MLCOE) partners across the firm to shape, create, and deploy Machine Learning Solutions for our most challenging business problems. This includes ensuring the quality, integrity, and security of the company's data, as well as leveraging this data to generate insights and drive decision-making. The CDAO is also responsible for developing and implementing solutions that support the firm's commercial goals by harnessing artificial intelligence and machine learning technologies to develop new products, improve productivity, and enhance risk management effectively and responsibly.</p><p>
As an intern within the MLCOE, you will apply sophisticated machine learning methods to a diverse range of complex domains, including natural language processing, large language models, speech recognition and understanding, reinforcement learning, and recommendation systems. You will collaborate closely with MLCOE mentors, business experts, and technologists, conducting independent research and deploying solutions into production. A strong passion for machine learning, solid expertise in deep learning with hands-on implementation experience, and a commitment to continuous learning and innovation are essential. This role offers a unique opportunity to contribute to and learn from a world-class machine learning team. Learn more about our MLCOE team at jpmorgan.com/mlcoe.</p><p>
Our Summer Associate Internship Program begins in June, depending on your academic calendar. Your professional growth and development will be supported throughout the internship program via project work related to your academic and professional interests, mentorship, an engaging speaker series with our senior leaders and more. Your project will have direct impact on JPMorgan's businesses, will be integrated into our product pipelines, or be part of published research in top AI/ML conferences. Full-time employment offers may be extended upon successful completion of the program within our hybrid work model.</p><p><b>
Job responsibilities</b></p><ul><li>
Research and explore new machine learning methods through independent study, attending industry-leading conferences, experimentation and participating in our knowledge sharing community</li><li>
Develop state-of-the art machine learning models to solve real-world problems and apply it to tasks such as natural language processing (NLP), speech recognition and analytics, time-series predictions or recommendation systems</li><li>
Collaborate with multiple partner teams such as Business, Technology, Product Management, Legal, Compliance, Strategy and Business Management to deploy solutions into production</li></ul><p>
</p><p><b>Required qualifications, capabilities, and skills</b></p><ul><li>
Enrolled in a PhD or MS in a quantitative discipline, e.g., Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, Data Science, or related fields, or equivalent research or industry experience,</li><li>
Expected graduation date of December 2026 through August 2027</li><li>
Solid background in NLP, large language models, speech recognition and modelling, or personalization/recommendation. Familiarity with state-of-the-art practice in these domains</li><li>
Proficient in Python, and experience with machine learning and deep learning toolkits (e.g., TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas)</li><li>
Scientific thinking, ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals</li><li>
Solid written and spoken communication to effectively communicate technical concepts and results to both technical, and business audiences</li><li>
Ability to work both independently and in highly collaborative team environments</li></ul><p><b>
Preferred qualifications, capabilities, and skills</b></p><ul><li>
Strong background in Mathematics and Statistics</li><li>
Familiarity with the financial services industries</li><li>
Published research in areas of natural language processing, deep learning, or reinforcement learning at a major conference or journal</li><li>
Ability to develop and debug production-quality code</li><li>
Familiarity with continuous integration models and unit test development</li><li>
Published research in areas of natural language processing, speech recognition, reinforcement learning, or deep learning at a major conference or journal</li></ul><p>
#MLCOE_jobs</p><p><br>
</p></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div><p></p><b>ABOUT US</b>
<br>
<br>
J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives.<br>
<div><div>We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.</div></div></div>

2026 Machine Learning Center of Excellence (NLP)-Internship

Google

<div><h3 class="jobSectionHeader"><b>Minimum qualifications:</b></h3><ul>
<li>Bachelor's degree in Computer Science or equivalent practical experience.</li>
<li>3 years of experience building machine learning solutions and working with technical customers.</li>
<li>Experience designing cloud enterprise solutions and supporting customer projects to completion.</li>
<li>Experience coding in one or more general purpose languages (e.g., Python, Java, Go, C or C++) including data structures, algorithms, and software design.</li></ul><br>
<h3 class="jobSectionHeader"><b>
Preferred qualifications:</b></h3><ul>
<li>Experience working with recommendation engines, data pipelines, or distributed machine learning.</li>
<li>Experience with deep learning frameworks (e.g., TensorFlow, XGBoost).</li>
<li>Understanding of the auxiliary practical concerns in production machine learning systems.</li>
<li>Knowledge of data warehousing concepts, including data warehouse technical architectures, infrastructure components, ETL/ ELT and reporting/analytic tools and environments (e.g., Apache Beam, Hadoop, Spark, Pig, Hive, MapReduce).</li>
</ul><div><h2 class="jobSectionHeader"><b>About the job</b></h2><p>
The Google Cloud Consulting Professional Services team guides customers through the moments that matter most in their cloud journey to help businesses thrive. We help customers transform and evolve their business through the use of Google&rsquo;s global network, web-scale data centers, and software infrastructure. As part of an innovative team in this rapidly growing business, you will help shape the future of businesses of all sizes and use technology to connect with customers, employees, and partners.</p><br>
<p>
As a Cloud AI Engineer, you will design and implement machine learning solutions for customer use cases, leveraging core Google products including TensorFlow, DataFlow, and Vertex AI. You will work with customers to identify opportunities to apply machine learning in their business, and travel to customer sites to deploy solutions and deliver workshops to educate and empower customers. You will work closely with product management and product engineering to build and constantly drive excellence in our products.<br>
<br>
In this role, you are the Google engineer working with Google's largest and most motivated Cloud customers. Together with the team you will support customer implementation of Google Cloud products through architecture guidance, best practices, data migration, capacity planning, implementation, troubleshooting, monitoring, and much more.</p><p><br>
Google Cloud accelerates every organization&rsquo;s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google&rsquo;s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.</p></div><div><h2 class="jobSectionHeader"><b>
Responsibilities</b></h2><ul>
<li>Be a trusted technical advisor to customers and solve complex machine learning challenges.</li>
<li>Coach customers on the practical challenges in machine learning systems feature extraction and feature definition, data validation, monitoring, and management of features and models.</li>
<li>Work with customers, partners, and Google Product teams to deliver tailored solutions into production.</li>
<li>Create and deliver best practice recommendations, tutorials, blog articles, and sample code.</li>
<li>Travel up to 30% for in-region for meetings, technical reviews, and onsite delivery activities.</li>
</ul></div>Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.</div>

AI Infrastructure Engineer

IMC Trading

<div>
 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.
 <br/>
 <br/>
 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&rsquo;s technology and trading capabilities.
 <br/>
 <br/>
 <strong>
  Your Core Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   The opportunity to be in a brand new position in a growing team
  </li>
  <li>
   Develop large-scale distributed training pipelines to manage datasets and complex models
  </li>
  <li>
   Build and optimize low-latency inference pipelines, ensuring models deliver real-time predictions in production systems
  </li>
  <li>
   Develop libraries to improve the performance of machine learning frameworks
  </li>
  <li>
   Maximize performance in training and inference using GPU hardware and acceleration libraries
  </li>
  <li>
   Design scalable model frameworks capable of handling high-volume trading data and delivering real-time, high-accuracy predictions
  </li>
  <li>
   Collaborate with quantitative researchers to automate ML experiments, hyperparameter tuning, and model retraining
  </li>
  <li>
   Partner with HPC specialists to optimize workflows, improve training speed, and reduce costs
  </li>
  <li>
   Evaluate and roll out third-party tools to enhance model development, training, and inference capabilities
  </li>
  <li>
   Dig into the internals of open-source ML tools to extend their capabilities and improve performance
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Your Skills And Experience
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   5+ years of experience in machine learning with a focus on training or inference systems
  </li>
  <li>
   Hands-on experience with real-time, low-latency ML pipelines in high-performance environments is a strong plus
  </li>
  <li>
   Strong engineering skills, including Python, CUDA, or C++
  </li>
  <li>
   Knowledge of machine learning frameworks such as PyTorch, TensorFlow, or JAX
  </li>
  <li>
   Proficiency in GPU programming for training and inference acceleration (e.g., CuDNN, TensorRT)
  </li>
  <li>
   Experience with distributed training for scaling ML workloads (e.g., Horovod, NCCL)
  </li>
  <li>
   Exposure to cloud platforms and orchestration tools
  </li>
  <li>
   A track record of contributing to open-source projects in machine learning, data science, or distributed systems is a plus
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  About Us
  <br/>
  <br/>
 </strong>
 IMC is a global trading firm powered by a cutting-edge research environment and a world-class technology backbone. Since 1989, we&rsquo;ve been a stabilizing force in financial markets, providing essential liquidity upon which market participants depend. Across our offices in the US, Europe, Asia Pacific, and India, our talented quant researchers, engineers, traders, and business operations professionals are united by our uniquely collaborative, high-performance culture, and our commitment to giving back. From entering dynamic new markets to embracing disruptive technologies, and from developing an innovative research environment to diversifying our trading strategies, we dare to continuously innovate and collaborate to succeed.
</div>


Machine Learning Engineer

PROXIMIE

<div><p>Proximie is on a mission to improve healthcare by transforming the world&rsquo;s operating rooms into connected ecosystems of people, devices, and data.</p><div><p>
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.</p><p>
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.</p><p>
Proximie was commercialised in 2019 and is available in over 500 facilities globally.</p><p>
Check out our Founder and CEO Nadine&rsquo;s Origins Story here: https://www.proximie.com/about-us/</p><p>
Position Overview</p><p>
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.</p><p>
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.</p><p>
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.</p><p>
Responsibilities</p><ul><li><p>
Collaborate with product, engineering and commercial teams to develop and deploy AI models for real world application in hospitals all over the world.</p></li><li><p>
Design, train and validate machine learning mono and multi-modal models using state of the art approaches.</p></li><li><p>
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.</p></li><li><p>
Own the full model lifecycle including but not limited to data curation, model implementation, training, validation, deployment, and maintenance.</p></li><li><p>
Development within Proximie environment to enable dynamic model training and performance evaluation while integrating with Proximie&rsquo;s data lakes.</p></li><li><p>
Document solutions and contribute to internal knowledge sharing and capability building.</p></li></ul><div><p>
Requirements</p><ul><li><p>
PhD in a machine learning field such as computer science, data science, engineering, or a related field. Masters considered but PhD preferred.</p></li><li><p>
Minimum of 4 years&rsquo; hands-on experience in industry, developing and deploying AI solutions which solve real-world problems.</p></li><li><p>
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.</p></li><li><p>
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.</p></li><li><p>
Proficiency with deep learning frameworks such as TensorFlow/PyTorch.</p></li><li><p>
Proficiency with Python and strong software development background.</p></li><li><p>
Knowledge and experience with AWS is highly desirable.</p></li><li><p>
Experience with MLOps practices, including versioning, deployment, and monitoring of models highly desirable.</p></li><li><p>
Ability to communicate complex technical concepts clearly to non-technical stakeholders.</p></li></ul><p>
Why Work for Proximie?</p><ul><li><p>
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.</p></li><li><p>
Generous annual leave.</p></li><li><p>
Two &ldquo;well-being&rdquo; days per year plus the day off for your birthday.</p></li><li><p>
&ldquo;Summer Fridays&rdquo; &ndash; early office closing on Fridays during summer months.</p></li><li><p>
Annual bonus programme &ndash; based on individual contribution.</p></li><li><p>
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.</p></li><li><p>
Flexible working hours - we trust our people to manage their time and to focus on wider results.</p></li><li><p>
A flat organizational structure where every opinion matters, ideas are cultivated, and innovation is encouraged.</p></li><li><p>
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.</p></li></ul><p>
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.</p></div></div></div>

Explore 82+ Machine learning researcher in London this July. Find roles across top companies and apply now to boost your career.

82 machine learning researcher jobs In London

Senior Data Scientist

Software Engineer – Machine Learning (AI Training)

Senior Machine Learning Engineer

2026 Machine Learning Center of Excellence (NLP)-Internship

AI Infrastructure Engineer

Machine Learning Engineer

Senior Machine Learning Engineer