machine learning engineer

software engineer

ai engineer

senior software engineer

full stack engineer

nlp engineer

<div>
 <strong>
  Your role
  <br/>
  <br/>
 </strong>
 Are you passionate about AI/ML, programming, and automation? Do you have technical expertise in design, software development, and modeling? Do you aspire to develop the next generation of AI business applications?
 <br/>
 <br/>
 As a Data Scientist, you will collaborate with our data science and business teams to build state-of-the-art models, and perform exploratory analysis on new and existing data to identify, investigate, and solve challenges. You should be comfortable applying a variety of techniques to find the best results and capable of researching new methods to trial. You will work closely within a small team where collaboration is key to achieving our common goals.
 <br/>
 <br/>
 <ul>
  <li>
   Collaborate with the business to assess opportunities for AI/data analytics technologies and maximize their value/impact for our clients.
  </li>
  <li>
   Support the design of AI/data analytics solution architecture and work with stakeholders to develop implementation roadmaps.
  </li>
  <li>
   Support AI/data analytics solution implementation and deployment.
  </li>
  <li>
   Develop, maintain, and deploy LLM, machine learning, and natural language processing pipelines and models with high performance, quality, and stability.
  </li>
  <li>
   Partner with the business to integrate AI and machine learning solutions across various strategic platforms. Models may span across a variety of domains, including but not limited to: LLM-based agentic AI architectures, natural language processing (e.g., document classification, named entity recognition, topic modeling, advanced and semantic information search, extraction), data analytics (predictive modeling, time-series analytics, pattern recognition, recommendation engines), computer vision (OCR), and voice recognition (speech-to-text).
  </li>
  <li>
   Research and build POCs for new and innovative AI solutions and technologies.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Job Type
  <br/>
  <br/>
 </strong>
 Full Time
 <br/>
 <br/>
 <strong>
  Job Reference #
  <br/>
  <br/>
 </strong>
 336118BR
 <br/>
 <br/>
 <strong>
  City
  <br/>
  <br/>
 </strong>
 London
 <br/>
 <br/>
 <strong>
  Your team
  <br/>
  <br/>
 </strong>
 You&rsquo;ll be working in the IB AI Center of Excellence team in London, focusing on building AI products across the Investment Bank. The AI solutions we build support our colleagues in working more efficiently, reducing the risks we face as a bank, and generating more revenues. Moreover, our products ensure that our clients receive timely and personalized content. As a Data Scientist, you&rsquo;ll play an important role in shaping the AI landscape within the IB.
 <br/>
 <br/>
 Diversity helps us grow together. That&rsquo;s why we are committed to fostering and advancing diversity, equity, and inclusion. It strengthens our business and brings value to our clients.
 <br/>
 <br/>
 <strong>
  Your expertise
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Master's degree or higher in a quantitative / scientific field or equivalent work experience
  </li>
  <li>
   Experience in designing and developing enterprise-scale AI and NLP solutions in the areas of Named Entity Recognition, Document Classification, Document Summarization, Topic Modeling, Sentiment Analysis, and OCR text processing.
  </li>
  <li>
   Experience building ML &amp; NLP solutions using common ML libraries and frameworks, including Pandas, Sklearn, TensorFlow, SparkML, Pytorch, etc.
  </li>
  <li>
   Skilled in end-to-end development of ML/NLP models (supervised &amp; unsupervised), including data cleaning, pipeline creation for structured/unstructured data, feature engineering, model selection/ensembles, evaluation metrics, visualization, and advanced statistical modeling (regression, spatial, time series).
  </li>
  <li>
   Ideally 2+ years of programming experience in one or more of the following: Python, R, Scala, C/C++, Matlab, SQL/Postgres, etc. Knowledge of CI/CD pipelines, Git, and GitHub/GitLab.
  </li>
  <li>
   Familiarity with Agentic AI frameworks such as LangGraph, AutoGen, etc is a plus
  </li>
  <li>
   Experience working in project-based teams, collaborating with colleagues, interacting with stakeholders, working to deadlines, and delivering projects that solve specific business problems.
  </li>
  <li>
   You&rsquo;re curious to explore how AI can improve how we build, deliver, and optimize workflows. You do this with sound judgment &ndash; validating outputs and aligning with policies, risk standards, and ethical use.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  About Us
  <br/>
 </strong>
 UBS is a leading and truly global wealth manager and the leading universal bank in Switzerland. We also provide diversified asset management solutions and focused investment banking capabilities. Headquartered in Zurich, Switzerland, UBS is present in more than 50 markets around the globe.
 <br/>
 <br/>
 We know that great work is never done alone. That&rsquo;s why we place collaboration at the heart of everything we do. Because together, we&rsquo;re more than ourselves. Want to find out more? Visit ubs.com/careers.
 <br/>
 <br/>
 <strong>
  Join us
  <br/>
  <br/>
 </strong>
 At UBS, we know that it's our people, with their diverse skills, experiences and backgrounds, who drive our ongoing success. We&rsquo;re dedicated to our craft and passionate about putting our people first, with new challenges, a supportive team, opportunities to grow and flexible working options when possible. Our inclusive culture brings out the best in our employees, wherever they are on their career journey. And we use artificial intelligence (AI) to work smarter and more efficiently. We also recognize that great work is never done alone. That&rsquo;s why collaboration is at the heart of everything we do. Because together, we&rsquo;re more than ourselves.
 <br/>
 <br/>
 We&rsquo;re committed to disability inclusion and if you need reasonable accommodation/adjustments throughout our recruitment process, you can always contact us.
 <br/>
 <br/>
 <strong>
  Disclaimer / Policy statements
  <br/>
  <br/>
 </strong>
 UBS is an Equal Opportunity Employer. We respect and seek to empower each individual and support the diverse cultures, perspectives, skills and experiences within our workforce.
</div>


Junior Data Scientist

<div><div><div><div>United Kingdom</div>
</div><div><div>Business management, administration and support
</div></div><div><div>Investment Bank
</div></div><div><p><b>Job Reference #</b></p>
<div>336118BR</div>
</div><div><p><b>City</b></p>
<div>London</div>
</div><div><p><b>Job Type</b></p>
<div>Full Time
</div></div><div><p><b>Your role</b></p>
<div>Are you passionate about AI/ML, programming, and automation? Do you have technical expertise in design, software development, and modeling? Do you aspire to develop the next generation of AI business applications?<br>
<br>
As a Data Scientist, you will collaborate with our data science and business teams to build state-of-the-art models, and perform exploratory analysis on new and existing data to identify, investigate, and solve challenges. You should be comfortable applying a variety of techniques to find the best results and capable of researching new methods to trial. You will work closely within a small team where collaboration is key to achieving our common goals.<br>
<br>
<ul><li>Collaborate with the business to assess opportunities for AI/data analytics technologies and maximize their value/impact for our clients.</li><li>Support the design of AI/data analytics solution architecture and work with stakeholders to develop implementation roadmaps.</li><li>Support AI/data analytics solution implementation and deployment.</li><li>Develop, maintain, and deploy LLM, machine learning, and natural language processing pipelines and models with high performance, quality, and stability.</li><li>Partner with the business to integrate AI and machine learning solutions across various strategic platforms. Models may span across a variety of domains, including but not limited to: LLM-based agentic AI architectures, natural language processing (e.g., document classification, named entity recognition, topic modeling, advanced and semantic information search, extraction), data analytics (predictive modeling, time-series analytics, pattern recognition, recommendation engines), computer vision (OCR), and voice recognition (speech-to-text).</li><li>Research and build POCs for new and innovative AI solutions and technologies.</li></ul></div>
</div><div><p><b>Your team</b></p>
<div>You&rsquo;ll be working in the IB AI Center of Excellence team in London, focusing on building AI products across the Investment Bank. The AI solutions we build support our colleagues in working more efficiently, reducing the risks we face as a bank, and generating more revenues. Moreover, our products ensure that our clients receive timely and personalized content. As a Data Scientist, you&rsquo;ll play an important role in shaping the AI landscape within the IB.<br>
<br>
Diversity helps us grow together. That&rsquo;s why we are committed to fostering and advancing diversity, equity, and inclusion. It strengthens our business and brings value to our clients.</div>
</div><div><p><b>Your expertise</b></p>
<ul><li>Master's degree or higher in a quantitative / scientific field or equivalent work experience</li><li>Experience in designing and developing enterprise-scale AI and NLP solutions in the areas of Named Entity Recognition, Document Classification, Document Summarization, Topic Modeling, Sentiment Analysis, and OCR text processing.</li><li>Experience building ML &amp; NLP solutions using common ML libraries and frameworks, including Pandas, Sklearn, TensorFlow, SparkML, Pytorch, etc.</li><li>Skilled in end-to-end development of ML/NLP models (supervised &amp; unsupervised), including data cleaning, pipeline creation for structured/unstructured data, feature engineering, model selection/ensembles, evaluation metrics, visualization, and advanced statistical modeling (regression, spatial, time series).</li><li>Ideally 2+ years of programming experience in one or more of the following: Python, R, Scala, C/C++, Matlab, SQL/Postgres, etc. Knowledge of CI/CD pipelines, Git, and GitHub/GitLab.</li><li>Familiarity with Agentic AI frameworks such as LangGraph, AutoGen, etc is a plus</li><li>Experience working in project-based teams, collaborating with colleagues, interacting with stakeholders, working to deadlines, and delivering projects that solve specific business problems.</li><li>You&rsquo;re curious to explore how AI can improve how we build, deliver, and optimize workflows. You do this with sound judgment &ndash; validating outputs and aligning with policies, risk standards, and ethical use.</li></ul>
</div><div><p><b>About us</b></p>
<div>UBS is a leading and truly global wealth manager and the leading universal bank in Switzerland. We also provide diversified asset management solutions and focused investment banking capabilities. Headquartered in Zurich, Switzerland, UBS is present in more than 50 markets around the globe.<br>
We know that great work is never done alone. That&rsquo;s why we place collaboration at the heart of everything we do. Because together, we&rsquo;re more than ourselves. Want to find out more? Visit ubs.com/careers.</div>
</div><div><p><b>Join us</b></p>
<div>At UBS, we know that it's our people, with their diverse skills, experiences and backgrounds, who drive our ongoing success. We&rsquo;re dedicated to our craft and passionate about putting our people first, with new challenges, a supportive team, opportunities to grow and flexible working options when possible. Our inclusive culture brings out the best in our employees, wherever they are on their career journey. And we use artificial intelligence (AI) to work smarter and more efficiently. We also recognize that great work is never done alone. That&rsquo;s why collaboration is at the heart of everything we do. Because together, we&rsquo;re more than ourselves.<br>
We&rsquo;re committed to disability inclusion and if you need reasonable accommodation/adjustments throughout our recruitment process, you can always contact us.</div>
</div><div><p><b>Disclaimer / Policy statements</b></p>
<div>UBS is an Equal Opportunity Employer. We respect and seek to empower each individual and support the diverse cultures, perspectives, skills and experiences within our workforce.</div></div></div></div><div></div>

Thomson Reuters

<div>
 Join a cutting-edge research team working to deliver on the transformation promises of modern AI. We are seeking Machine Learning Research Engineers with the skills and drive to build and conduct experiments with advanced AI systems in an academic environment rich with high-quality data from real-world problems.
 <br/>
 <br/>
 Foundational Research is the dedicated core Machine Learning research division of Thomson Reuters. We are focused on research and development, with a particular focus on advanced algorithms and training techniques for Large Language Models (LLMs). We are expanding our strong foundation of research capabilities across different areas and are looking for engineers who participate in designing, coding, conducting experiments, and translating findings into concrete deliverables.
 <br/>
 <br/>
 <strong>
  Our Focus Areas Are
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   LLM Training (Continued pretraining, instruction tuning, reinforcement learning, distributed training, efficient ML techniques)
  </li>
  <li>
   Post-training techniques for planning, reasoning &amp; complex workflows (e.g., reasoning models, LLMs + knowledge graphs, test time compute, CoT pipelines, tool use &amp; API calling, etc.)
  </li>
  <li>
   Data-centric Machine Learning (Synthetic data, curriculum learning, learned data mixtures, etc.)
  </li>
  <li>
   Evaluation (Benchmarking best practices, humans/LLMs as a judge, red teaming/adversarial testing, hallucination detection, etc.)
   <br/>
   <br/>
  </li>
 </ul>
 We work collaboratively with TR Labs (TR's applied research division), academic partners at world-leading research institutions, and subject matter experts with decades of experience. We experiment, prototype, test, and deliver ideas in the pursuit of smarter and more valuable models trained on an unprecedented wealth of data and powered by state-of-the-art technical infrastructure. Through our unique institutional experience, we have access to an unprecedented number of subject matter experts involved in data collection, testing and evaluation of trained models.
 <br/>
 <br/>
 As an ML Research Engineer, you will play a key part in a diverse global team of experts. We hire world-leading specialists in ML/NLP/GenAI, as well as Engineering, to drive the company's leading internal AI model development. You will have the opportunity to contribute to our proprietary AI model research &amp; development through rapid prototyping, scalable infrastructure, and production-quality implementations, and to research papers in top tier academic conferences and journals.
 <br/>
 <br/>
 <strong>
  About The Role
  <br/>
  <br/>
 </strong>
 In this opportunity, as an ML Research Engineer you will:
 <br/>
 <br/>
 <ul>
  <li>
   Build: You will design and implement robust, scalable systems for training and evaluating large language models. You'll build data pipelines for data-centric research, training infrastructure for instruction fine-tuning (IFT), Direct Preference Optimization (DPO), and reinforcement learning workflows, evaluation frameworks for comprehensive model assessment, and infrastructure for agentic workflows that enables researchers to iterate quickly and effectively.
  </li>
  <li>
   Innovate: You will work at the very cutting edge of AI Research at an institution with some of the richest data sources in the world. Through your work, you will rapidly implement novel research ideas in LLM training, evaluation, agentic systems, and data processing, transforming them into production-ready systems and research publications. You will contribute to advancing the state-of-the-art in data-centric ML by building tools that help us make the best use of our unprecedented data resources.
  </li>
  <li>
   Experiment and Develop: You are involved in the entire research &amp; model development lifecycle, brainstorming, coding, testing, and delivering high-quality implementations that support cutting-edge research. You'll build pipelines for synthetic data generation, automated evaluation systems, training workflows for various fine-tuning approaches, and agent-based workflows that push the boundaries of what's possible with LLMs.
  </li>
  <li>
   Collaborate: Working on a collaborative global team of research engineers and scientists both within Thomson Reuters and our academic partners at world-leading universities. You'll work closely with researchers to understand their needs and translate cutting-edge research papers into practical, scalable implementations.
  </li>
  <li>
   Communicate: Actively engage in sharing technical implementations and best practices with the wider team through code reviews, documentation, technical presentations, and knowledge sharing sessions. Contribute to internal research discussions and stay current with the latest developments in LLM training, evaluation, agentic AI, and data-centric machine learning.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  About You
  <br/>
  <br/>
 </strong>
 You're a fit for the role if your background includes:
 <br/>
 <br/>
 <strong>
  Required Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Bachelor's or Master's degree in Computer Science, Engineering, or a relevant discipline (or equivalent practical experience)
  </li>
  <li>
   3+ years of hands-on experience building ML/NLP/AI systems with strong software engineering practices
  </li>
  <li>
   Demonstrated expertise in building production-quality code and data pipelines for ML systems
  </li>
  <li>
   Proficiency in modern AI development frameworks including: PyTorch, Jax , HuggingFace Transformers, LLM APIs (litellm etc) and vLLM for building and deploying large-scale AI applications
  </li>
  <li>
   Understanding of LLM training methodologies including instruction fine-tuning, preference optimization, and reinforcement learning approaches
  </li>
  <li>
   Strong software engineering skills including version control, testing, CI/CD, and code quality practices
  </li>
  <li>
   Hands-on experience with experiment tracking and orchestration tools such as clearml, Weights &amp; Biases, MLflow.
  </li>
  <li>
   Experience with distributed computing frameworks and large-scale data processing (e.g., Ray, Spark, Dask)
  </li>
  <li>
   Excellent communication skills to collaborate with researchers and translate research ideas into robust implementations
  </li>
  <li>
   Self-driven attitude with genuine curiosity about ML research developments
  </li>
  <li>
   Comfortable working in fast-paced, agile environments, managing the uncertainty and ambiguity of genuinely novel research
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Helpful Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Track record of ML impact in the form of releases, publications or contributions to open source ML libraries or frameworks (especially in training, evaluation, data processing, or agent systems)
  </li>
  <li>
   Experience building and maintaining ML training infrastructure and data pipelines at scale
  </li>
  <li>
   Extensive experience with LLM training techniques such as instruction fine-tuning (IFT), Direct Preference Optimization (DPO), Proximal Policy Optimization (PPO), or other RLHF methods
  </li>
  <li>
   Hands-on experience implementing and scaling supervised fine-tuning, preference learning, and reinforcement learning pipelines for LLMs
  </li>
  <li>
   Experience building LLM evaluation frameworks, benchmarking systems, or automated testing pipelines
  </li>
  <li>
   Hands-on experience with agentic workflows, tool-using AI systems, or multi-agent coordination (examples include: langgraph, AutoGPT, LLamaIndex)
  </li>
  <li>
   Experience with data-centric ML approaches including synthetic data generation, data curation, or curriculum learning pipelines
  </li>
  <li>
   Experience training large-scale models over distributed nodes with cloud tools such as AWS, MS Azure, or Google Cloud
  </li>
  <li>
   Hands-on experience with MLOps, experiment tracking, and model deployment systems
  </li>
  <li>
   Strong interest in staying current with ML research literature and ability to quickly implement novel techniques from academic papers
  </li>
  <li>
   Familiarity with training optimization techniques such as mixed precision training, gradient checkpointing, and efficient attention mechanisms
  </li>
  <li>
   Knowledge of modern ML engineering practices (containerization, orchestration, monitoring)
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  You Will Enjoy
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Learning and development: On-the-job coaching and learning as well as the opportunity to work with cutting-edge methods and technologies.
  </li>
  <li>
   Plenty of data, compute, and high-impact problems: Our scientists and engineers get to explore large datasets and discover new capabilities and insights. Thomson Reuters is best known for the globally respected Reuters News agency, but our company is also the leading source of information for legal, corporate, and tax &amp; accounting professionals. We have over 60,000 TBs worth of legal, regulatory, news, and tax data. We also provide access to significant cloud computing resources for our researchers and engineers.
  </li>
  <li>
   Competitive compensation &amp; benefits packages
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  What&rsquo;s in it For You?
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Hybrid Work Model: We&rsquo;ve adopted a flexible hybrid working environment (2-3 days a week in the office depending on the role) for our office-based roles while delivering a seamless experience that is digitally and physically connected.
  </li>
  <li>
   Flexibility &amp; Work-Life Balance: Flex My Way is a set of supportive workplace policies designed to help manage personal and professional responsibilities, whether caring for family, giving back to the community, or finding time to refresh and reset. This builds upon our flexible work arrangements, including work from anywhere for up to 8 weeks per year, empowering employees to achieve a better work-life balance.
  </li>
  <li>
   Career Development and Growth: By fostering a culture of continuous learning and skill development, we prepare our talent to tackle tomorrow&rsquo;s challenges and deliver real-world solutions. Our Grow My Way programming and skills-first approach ensures you have the tools and knowledge to grow, lead, and thrive in an AI-enabled future.
  </li>
  <li>
   Industry Competitive Benefits: We offer comprehensive benefit plans to include flexible vacation, two company-wide Mental Health Days off, access to the Headspace app, retirement savings, tuition reimbursement, employee incentive programs, and resources for mental, physical, and financial wellbeing.
  </li>
  <li>
   Culture: Globally recognized, award-winning reputation for inclusion and belonging, flexibility, work-life balance, and more. We live by our values: Obsess over our Customers, Compete to Win, Challenge (Y)our Thinking, Act Fast / Learn Fast, and Stronger Together.
  </li>
  <li>
   Social Impact: Make an impact in your community with our Social Impact Institute. We offer employees two paid volunteer days off annually and opportunities to get involved with pro-bono consulting projects and Environmental, Social, and Governance (ESG) initiatives.
  </li>
  <li>
   Making a Real-World Impact: We are one of the few companies globally that helps its customers pursue justice, truth, and transparency. Together, with the professionals and institutions we serve, we help uphold the rule of law, turn the wheels of commerce, catch bad actors, report the facts, and provide trusted, unbiased information to people all over the world.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  About Us
  <br/>
  <br/>
 </strong>
 Thomson Reuters informs the way forward by bringing together the trusted content and technology that people and organizations need to make the right decisions. We serve professionals across legal, tax, accounting, compliance, government, and media. Our products combine highly specialized software and insights to empower professionals with the data, intelligence, and solutions needed to make informed decisions, and to help institutions in their pursuit of justice, truth, and transparency. Reuters, part of Thomson Reuters, is a world leading provider of trusted journalism and news.
 <br/>
 <br/>
 We are powered by the talents of 26,000 employees across more than 70 countries, where everyone has a chance to contribute and grow professionally in flexible work environments. At a time when objectivity, accuracy, fairness, and transparency are under attack, we consider it our duty to pursue them. Sound exciting? Join us and help shape the industries that move society forward.
 <br/>
 <br/>
 As a global business, we rely on the unique backgrounds, perspectives, and experiences of all employees to deliver on our business goals. To ensure we can do that, we seek talented, qualified employees in all our operations around the world regardless of race, color, sex/gender, including pregnancy, gender identity and expression, national origin, religion, sexual orientation, disability, age, marital status, citizen status, veteran status, or any other protected classification under applicable law. Thomson Reuters is proud to be an Equal Employment Opportunity Employer providing a drug-free workplace.
 <br/>
 <br/>
 We also make reasonable accommodations for qualified individuals with disabilities and for sincerely held religious beliefs in accordance with applicable law. More information on requesting an accommodation here.
 <br/>
 <br/>
 Learn more on how to protect yourself from fraudulent job postings here.
 <br/>
 <br/>
 More information about Thomson Reuters can be found on thomsonreuters.com.
 <br/>
 <br/>
</div>


Machine Learning Research Engineer (Foundational Research)

reddit

<div><div><div><div><div><div><div><div>Reddit is a community of communities. It's built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet's largest sources of information. For more information, visit www.redditinc.com.</div>
</div>
</div></div></div></div></div><p><b>Location: </b>Reddit has a flexible first workforce. Don't live near our office? No worries: you can work remotely from anywhere in the UK or the Netherlands.</p>
<p>
The <b>Ads Foundational Representations (AFR)</b> team develops signals and representations of Reddit's core entities (ads, posts, users, and so on), capturing the semantic, contextual, and behavioral information that Reddit Ads needs. We work on building embeddings to understand content and users' interests based on the content they engage with.</p>
<p>
Our team has the potential to highlight one of Reddit's biggest differentiators: genuinely curated, high-quality, extremely relevant, and daily updated organic content. We are a Machine Learning/Data heavy team with a focus on the following areas:</p>
<ul>
<li><b>Multimodal &amp; Content Embeddings</b> - Make sense of organic (posts, comments, subreddits) and promoted (ads, shopping products, their landing pages) text and media content by embedding them into a shared space.</li>
<li><b>Contextual and Behavioral Relevance </b>- Working with Product &amp; Data Science, establishing definitions of what ads are relevant to users and the content we show them next to, building metrics and fine-tuning embeddings to better reflect relevance.</li>
<li><b>Knowledge Graph Embeddings -</b> Building representations for the Knowledge graph entities, e.g., intellectual properties/brands, to be used for high-precision targeting &amp; business insights.</li>
<li><b>User Intent Modeling -</b> Leveraging various techniques to introduce user representations based on the content they interact with: batch &amp; real-time sequence modeling, LLM summarization, etc.</li>
<li><b>LLM-based Representations</b> - Leveraging LLMs, VLMs, and foundational models to build complex representations of Reddit entities that improve ranking outcomes</li>
</ul>
<p>The signals and features we create become a key piece in the Ads Delivery funnel, from targeting to the auction, as well as the Business Insights product and other advertiser-facing products such as Creative generation and optimization.</p>
<p>
As a <b>Senior ML Engineer</b>, you'll be in charge of the full-cycle execution of ML projects - from collaborating with cross-functional teams on requirements and design, to the implementation of the feature and its experimentation.</p>
<p><b>
Responsibilities</b></p>
<ul>
<li>Developing new or iterating on existing embedding models for advertising use cases, ranging from aggregation pipelines to two-tower architectures and sequence models.
</li><li>Working with local and 3rd-party LLMs/VLMs: extract representations, develop evaluation methodologies, prompt tune and fine-tune large models to build state-of-the-art embeddings.</li>
<li>Building data processing and inference pipelines for the models we develop.</li>
<li>Qualitative and quantitative evaluation of the various features we develop, end-to-end experimentation from internal benchmarks to downstream recommender system offline metrics to online experiments.</li>
<li>Ensuring the reliability, scalability, and performance of the ML systems by writing automated tests, monitoring performance, and implementing best practices for model management.</li>
<li>Participating in modeling and coding reviews: You will review work by other team members and provide feedback to ensure that it meets the team's standards for quality and performance.</li>
<li>Collaborating with cross-functional teams to understand business requirements and translate them into technical solutions.</li>
</ul>
<p><b>Required Qualifications:</b></p>
<ul>
<li>5+ years of hands-on experience with the full lifecycle of designing, training, evaluating, testing, and deploying industry-level models.</li>
<li>Experience building NLP or CV models and integrating them at scale.</li>
<li>Experience developing complex features/embeddings for downstream models.</li>
<li>Experience with mainstream DL frameworks: PyTorch or TensorFlow.</li>
<li>Excitement about working with data and readiness to look behind the metric numbers.</li>
</ul>
<p><b>Preferred Qualifications:</b></p>
<ul>
<li>Experience with our stack (Python, Pytorch, Airflow, BigQuery, Ray, k8s, kafka, GCP)</li>
<li>Familiarity with the Ads domain and/or Search/Recommender systems is a strong plus.</li>
<li>Tech leadership experience: mentoring junior engineers and leading complex projects.</li>
<li>Hands-on experience with using/fine-tuning/building LLMs.</li>
</ul>
<p><b>Benefits:</b></p>
<ul>
<li>Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support</li>
<li>Family Planning Support</li>
<li>Gender-Affirming Care</li>
<li>Mental Health &amp; Coaching Benefits</li>
<li>Group Personal Pension Scheme with Employer match</li>
<li>Private Medical and Dental Scheme</li>
<li>Income Replacement Programs</li>
<li>Bike to Work scheme</li>
<li>Flexible Vacation &amp; Paid Volunteer Time Off</li>
<li>Generous Paid Parental Leave</li>
</ul><div><p>
In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.</p>
<p>
During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors.</p>
<p><i>
Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.</i></p></div></div>

Senior Machine Learning Engineer, Ads Foundational Representations

Information Tech Consultants

<div>
 <p>
  <strong>
   Job Title:
  </strong>
  Data Scientist/Machine Learning Engineer
 </p>
 <p>
  <strong>
   Location:
  </strong>
  UK
 </p>
 <p>
  <strong>
   Experience:
  </strong>
  2&ndash;5 years
 </p>
 <p>
  <strong>
   Education:
  </strong>
  Master's in Science (IT/Computer Science/Engineer)
 </p>
 <p>
  <strong>
   Employment Type:
  </strong>
  Full-Time
 </p>
 <p>
  <strong>
   UK based candidates only.
  </strong>
 </p>
 <p>
  Information Tech Consultants Ltd (ITC) is an IT management and consulting firm based in Central London. Information Tech Consultants Ltd (ITC) is an IT management and consulting firm based in Central London. We are responsible for sourcing and hiring field experts for various companies. We primarily work with Software and Cloud Hosted Services organizations as well as Mobile Apps and Service companies.
 </p>
 <p>
  <strong>
   Required Skills:
  </strong>
 </p>
 <ul>
  <li>
   2-4 years of experience in Data science/Machine learning models from coding to deployment.
  </li>
  <li>
   Work with datasets using Python or R, SQL, No SQL.
  </li>
  <li>
   Assist in developing predictive and statistical models
  </li>
  <li>
   Write and optimize queries using SQL.
  </li>
  <li>
   Familiarity with data manipulation libraries (Pandas, NumPy), Understanding of statistics and probability.
  </li>
  <li>
   Hands-on experience with ML libraries like Scikit-learn, TensorFlow, or PyTorch.
  </li>
 </ul>
 <p>
  <strong>
   Preferred Skills:
  </strong>
 </p>
 <ul>
  <li>
   Hands on experience in coding (mandatory python and SQL or C++).
  </li>
  <li>
   Understanding of Generative AI, Computer Vision cloud technology, NLP, Deep Learning.
  </li>
  <li>
   Familiarity working with large data sets.
  </li>
  <li>
   Project Management background preferred.
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Qualifications :
  </strong>
 </p>
 <ul>
  <li>
   <strong>
    Master&rsquo;s (Required)
   </strong>
   in Data Science, Mathematics, Statistics, Economics, IT related fields and 2- 4 years of experience in Information Technology.
  </li>
  <li>
   You should be entitled to work in the UK with legal work authorization status.
  </li>
  <li>
   Must be willing to travel within the UK as per project/client requirements.
  </li>
  <li>
   Excellent communication skills and teamwork skills.
  </li>
 </ul>
 <p>
 </p>
</div>


Machine Learning Engineer

Fuse Energy

<div>
 Fuse Energy is a forward-thinking renewable energy startup on a mission to deliver a terawatt of renewable energy - fast. We're combining first-principles thinking with cutting-edge technology to build a radically better energy system. We raised $210M from top-tier investors including Multicoin, Balderton, Lakestar, Accel, Creandum, Lowercarbon, Ribbit, Box Group and strategic angels like Nico Rosberg, the Co-Founder of Solana and GPs behind Meta, Revolut, Spotify, Uber and more.
 <br/>
 <br/>
 We're creating a fully integrated energy company: from developing solar, wind and hydrogen projects to real-time power trading and distributed energy installations. By selling directly to consumers, we cut out the middleman, lower costs and pass on savings to customers.
 <br/>
 <br/>
 But we're not stopping there. We're also building the Energy Network: a decentralised platform of smart devices to electrify our homes, shifting usage to off-peak hours and helping balance the grid. This network strengthens grid stability - a critical foundation for scaling AI data centers and other energy-intensive industries.
 <br/>
 <br/>
 We're now looking to establish a cutting-edge AI team. As an Applied AI Engineer, this position is ideal for someone who possesses the technical expertise of a backend engineer but is specifically interested in applied AI and how it can be used to enhance the energy experience for our customers and our internal operations. You'll be working on a variety of exciting projects, including consumer-focused features like the Energy Co-Pilot and the Speedy Onboarding process (leveraging tools such as VLM/LLM). You will also collaborate across teams to build AI tools that enhance productivity and streamline processes within Fuse.
 <br/>
 <br/>
 <strong>
  Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Design, develop and deploy AI-powered features that directly impact consumer experiences, including personalised energy recommendations and seamless onboarding via AI models (e.g. using energy bills for quick setup)
  </li>
  <li>
   Build and optimise internal AI tools that will make the whole company more productive with a focus on automation and enhancing workflows
  </li>
  <li>
   Collaborate with backend engineers and data scientists to integrate AI-driven features into our platforms
  </li>
  <li>
   Collaborate with the trading and operations teams to ensure AI models are aligned with real-time market conditions and energy pricing
  </li>
  <li>
   Improve AI models to optimise trading strategies by anticipating market shifts based on weather and demand forecasts
  </li>
  <li>
   Stay up to date with the latest advancements in applied AI and machine learning and apply them to solve real-world problems within the energy space
  </li>
  <li>
   Monitor the performance of AI tools and models, ensuring they are functioning efficiently and effectively
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Requirements
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Minimum 3 years of engineering experience
  </li>
  <li>
   Proven experience as a Backend Engineer with a strong interest and practical experience in applied AI or machine learning
  </li>
  <li>
   Strong programming skills in Python (or similar languages) with familiarity in AI/ML libraries (TensorFlow, PyTorch, etc.)
  </li>
  <li>
   Experience working with large-scale models (LLMs/VLMs) and deploying AI-driven solutions into production
  </li>
  <li>
   Solid understanding of cloud technologies, containerisation and building scalable AI applications
  </li>
  <li>
   Ability to integrate AI/ML models into real-world applications, focusing on usability and performance
  </li>
  <li>
   Strong problem-solving skills and a practical approach to implementing AI solutions in a fast-paced environment
  </li>
  <li>
   Experience working with large datasets, particularly in relation to demand and supply forecasting
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Bonus
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Experience or strong interest in energy markets and trading strategies
  </li>
  <li>
   Understanding of weather forecasting, energy demand patterns, and production modelling
  </li>
  <li>
   Exposure to Natural Language Processing (NLP) or other related fields
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Benefits
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Competitive salary and an equity sign-on bonus
  </li>
  <li>
   Biannual bonus scheme
  </li>
  <li>
   Fully expensed tech to match your needs
  </li>
  <li>
   Paid annual leave
  </li>
  <li>
   Breakfast and dinner allowance for office based employees
  </li>
 </ul>
</div>


Applied AI Engineer

Xantura

<div><h3 class="jobSectionHeader"><b>Description</b></h3><div><br>
In this role you will work in the Platform team &ndash; a function for the deployment and evolution of the backend platform that underpins the core of the Xantura business.</div><br>
<h3 class="jobSectionHeader"><b>
Key Responsibilities</b></h3><div><br>
As an MLOps Engineer, you'll own the infrastructure layer that all of Xantura's AI services depend on to operate and scale. You'll be responsible for how ML models and NLP systems are deployed, monitored, and maintained across a growing base of local authority clients, ensuring that what works for one client works reliably for a hundred.<br>
</div><div>
<br>
You'll work across every pillar of the AI function - predictive modelling, text analytics, knowledge representation, and agentic AI - building the deployment pipelines, orchestration, and observability that enable the rest of the engineering team to ship with confidence.<br>
</div><div>
<br>
<b>Key responsibilities</b><br>
</div><ul><li>Continuously evolve the platform infrastructure powering all AI services (predictive modelling, NLP, knowledge representation, and agentic AI), ensuring reliable, scalable operation across a growing base of local authority clients.</li>
<li>Deploy and manage ML models via Azure ML endpoints, batch endpoints , and AKS, enabling resilient, secure model hosting that accelerates client onboarding and ensures models remain performant and monitorable throughout their lifecycle.</li>
<li>Ensure all ML systems are transparent, explainable, and auditable, aligned with Responsible AI principles and UK GDPR; essential where AI outputs inform decisions about vulnerable people in health and social care.</li>
<li>Design, build, and maintain production-grade orchestration pipelines (Dagster) supporting model training, inference, and retraining, ensuring data from local authority systems is timely, accurate, and fit for purpose before it reaches ML services.</li>
<li>Contribute to organisation-wide AI capability building, sharing best practice with delivery and consulting teams, advising on technical feasibility, and shaping governance standards as the AI function scales.</li></ul><div><br>
</div><br>
<h3 class="jobSectionHeader"><b>What are we looking for?<br>
</b></h3><br>
<div>We&rsquo;d love to hear from you if you have:</div><ul>
<li>Bachelor's or Master's degree in Computer Science, Software Engineering, or a related technical field, or equivalent practical experience.</li>
<li>4+ years of professional experience in an MLOps, Platform Engineering, or Infrastructure Engineering role supporting ML or data-intensive systems.</li>
<li>Strong programming skills and production experience in Python.</li>
<li>Expertise in Azure-native MLOps, including model endpoints, pipelines, registries, environments, and compute management.</li>
</ul><div>Clear evidence of practical experience across the following:</div><ul>
<li>Deploying, scaling, and troubleshooting containerised workload on Kubernetes in production</li>
<li>Building and maintaining CI/CD pipelines (Azure DevOps or equivalent) for automated testing, building, and deployment of ML services</li>
<li>Implementing infrastructure-as-code (Terraform, Bicep or Pulumi)</li>
<li>Implementing monitoring and observability for production systems, including metrics, altering, logging, and dashboarding (e.g. Prometheus, Grafana)</li>
<li>Pipeline orchestration using Dagster, Airflow, Prefect, or similar</li>
</ul><div>
<br>
Bonus points if you have:</div><ul>
<li>Practical experience with model serving infrastructure &ndash; batch and/or real-time inference at scale.</li>
<li>Experience operating multi-tenant systems, particularly scaling infrastructure across multiple clients or business units.</li>
<li>Practical experience building and serving production-ready, asynchronous APIs for embedding and/or other compute-intensive services.</li>
<li>Experience setting up, and optimising vector databases, e.g. Qdrant, and integrating with other services</li>
<li>Proficiency in Python for building high-performance data and model pipelines, with strong software engineering discipline (testing, versioning, CI/CD).</li>
<li>Deep familiarity with the Azure ecosystem (Azure Kubernetes Service, Azure Container Registry, Azure DevOps, Azure Blob Storage, Azure Monitor, Azure Key Vault).</li>
</ul><div>
<br>
<b>Location &ndash;</b> This is a hybrid role based in our office in London (Borough). You would be expected to be able to work from the office at least 1-2 days per week. Some travel is also required for on-site client engagements as needed.</div><h3 class="jobSectionHeader"><b><br>
What can we offer you?</b></h3><br>
<ul>
<li>
Competitive salary reviewed annually</li>
<li>Work for a passionate, mission-driven company solving society&rsquo;s big problems</li>
<li>Work flexible hours around life commitments with a focus on delivering company value rather than hours worked</li>
<li>Ability to work remotely (excluding face-to-face Team Meetings and client meetings)</li>
<li>Training and development opportunities</li>
<li>25 days annual leave (plus bank holidays)</li>
<li>Company pension</li>
<li>Private medical insurance</li>
<li>Generous enhanced parental leave policies</li>
<li>Cycle to work scheme</li>
<li>Flu Vaccinations,</li>
<li>Eye Test and contribution towards Glasses for VDU use</li>
<li>Employee Assistance Programme<ul>
<li>Mental health and wellbeing support</li>
<li>Remote GP access</li>
<li>Counselling/therapy</li>
<li>Physiotherapy</li>
<li>Medical second opinions</li></ul><br>
</li>
</ul><br>
<h3 class="jobSectionHeader"><b>About Xantura</b></h3><div>
At Xantura, we&rsquo;re on a mission to reduce societal inequality by helping local authorities use data more effectively. Our AI-driven platform empowers frontline workers with the insights they need to prevent complex issues like homelessness or children being taken into care &mdash; before they happen. We make this possible by connecting siloed datasets, applying advanced machine learning to enrich the data, and using predictive analytics to identify those most at risk. Our platform then distills this into clear, actionable insights that help frontline staff intervene early and make a real difference.<br>
<br>
It&rsquo;s an exciting time to join Xantura. We&rsquo;re scaling quickly, bringing on new clients, strengthening our platform, and expanding into new areas. While we&rsquo;re a technology company at heart, our true focus is on improving lives &mdash; and we&rsquo;re looking for people who share that vision.</div></div>

Senior ML Ops Engineer

Explore 396+ Nlp engineer in London this July. Find roles across top companies and apply now to boost your career.

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