software engineer

data engineer

ai engineer

machine learning engineer

senior software engineer

computer vision engineer

Haystack

<div>
 We are working with a pioneering technology firm that is at the forefront of developing cutting-edge AI solutions for real-world applications across various industries. This company is renowned for its innovative approach to machine learning and its commitment to pushing the boundaries of what's possible.
 
 
 The Role
 
 
 <ul>
 <li>
 Develop, train, and optimise advanced computer vision and machine learning systems
 </li>
 <li>
 Deploy machine learning solutions in constrained edge environments
 </li>
 <li>
 Work with a team of experts on innovative AI projects
 </li>
 <li>
 Contribute to the full lifecycle of machine learning model development
 
 
 </li>
 </ul>
 What You'll Need
 
 
 <ul>
 <li>
 Proven experience as a Machine Learning Engineer
 </li>
 <li>
 Expertise in computer vision and machine learning model development
 </li>
 <li>
 Familiarity with deploying models in edge environments
 </li>
 <li>
 Strong problem-solving skills and an analytical mindset
 </li>
 <li>
 Excellent communication and collaboration abilities
 
 
 </li>
 </ul>
 What's On Offer
 
 
 <ul>
 <li>
 Competitive salary based on experience
 </li>
 <li>
 Opportunity to work on groundbreaking AI technology
 </li>
 <li>
 Diverse and inclusive work environment
 </li>
 <li>
 Professional growth and development opportunities
 
 
 </li>
 </ul>
 Apply via Haystack today!
 
 
</div>

Machine Learning Engineer

iProov

ML Engineer
 About iProov
 iProov provides science-based biometric solutions that enable the world’s most security-conscious organizations to streamline secure remote onboarding and authentication for digital and physical access. Our award-winning liveness technology and iSOC offer unmatched resilience against deepfakes and generative AI threats while ensuring effortless, scalable user experiences. Trusted by leading governments and enterprises, including the U.S. Department of Homeland Security, U.K. Home Office, GovTech Singapore, ING, and UBS, iProov sets the standard in biometric identity assurance.
 This global trust is built not only on our technology but on the strength of the people behind it. For us, diversity at iProov is about reflecting the customers we serve, holding the principles of equality and inclusion at the heart of everything we do and all that we stand for, embracing differences, creating possibilities, and growing together. We aim to foster a culture where individuals of all backgrounds feel confident in bringing their whole selves to work, feel included, and their talents are nurtured, empowering them to contribute fully to our purpose.
 
The Role
 Reports to: Head of Core AI
 Location: WeWork Waterloo - Hybrid
 Comp: Negotiable (Base) + Company Performance Bonus (10%) + Share Options + UK iProov Benefits
 
iProov is looking for a Machine Learning Engineer to join our Core AI team. You will be responsible for working on the biometric systems, developing new techniques and algorithms ensuring security and performance.
 How you can make an impact 
 <ul>
<li>Drive research projects in the areas of computer vision, machine learning and biometrics.</li>
<li>Research new biometric systems and contribute to prototyping new products - by testing and integrating existing technologies or by designing a new solution.</li>
<li>Develop and train deep learning models for face verification, liveness and attack detection.</li>
<li>Improve upon data and evaluation strategies, including synthetic and adversarial data.</li>
<li>Investigate failure modes and improve generalisation, robustness and fairness.</li>
<li>Collaborate cross-functionally to turn models into production-quality services.</li>
</ul>
What we would like to see from you
 <ul>
<li>A Masters or PhD in a numerate discipline such as Computer Science, Engineering, Computational Neuroscience.</li>
<li>Proven proficiency or experience in machine learning and computer vision.</li>
<li>Enjoys collaborating with cross-functional teams.</li>
<li>Proficiency in Python and modern deep learning frameworks.</li>
<li>Strong problem-solving skills and out-of-box thinking.</li>
</ul>
Extras: 
<ul>
<li>Experience working on 0- &gt;1 products.</li>
<li>Experience generating and using synthetic data</li>
</ul>
Benefits
 <ul>
<li>25 days Annual Leave, plus 8 Bank Holidays (more holiday with service - up to an extra 5 days off per year based on your continuous service)</li>
<li>Growth Shares allocated after passing probation (6 months of service)</li>
<li>Salary sacrifice schemes including: Pension, Cycle To Work and Electric Car Scheme</li>
<li>Nursery Sacrifice Scheme</li>
<li>Work Overseas Perk - Work globally for up to 2 weeks</li>
<li>Life Assurance</li>
<li>SmartHealth - Access to private GP, Psychologist, Nutritionist along with tailored fitness plans for both you and your family</li>
<li>Benefit from personalized 1:1 career coaching with our in-house Occupational Psychologist</li>
<li>Award winning L&D platform with personal allocated training budgets</li>
<li>Enhanced paid family leave</li>
<li>Pension - 5% employee, 3% employer</li>
<li>Flexible hybrid working environment</li>
<li>Free Barista Coffee/Tea, biscuits with fruit in the WeWork office</li>
<li>Free access to WeWork discounts and free online well-being sessions</li>
<li>Vitality Health - a range of options available on this below</li>
</ul>
The Vitality Programme includes a number of reward benefits that all employees have access to as part of the plan, for example:
 <ul>
<li>Private Health cover including Dental, Optical, and Audiology</li>
<li>50% off monthly gym memberships</li>
<li>Apple watches significantly discounted based member vitality status</li>
<li>Half price trainers with Runners Need</li>
<li>Weekly rewards – Free coffee with Café Nero</li>
<li>Monthly rewards – Free Cinema ticket</li>
<li>Discounts on travel with Expedia (hotels) and Mr & Mrs Smith with discounts getting greater throughout the year based on a members vitality status</li>
<li>Amazon prime free months based on activity</li>
<li>Up to 25% cashback at Waitrose when buying healthy foods</li>
<li>75% off stays at Champneys Health Spas</li>
<li>Allen Carr’s £299 no smoking programme for free</li>
<li>Access to Vitality Healthy Mind with 30% off Headspace subscriptions and the ability to earn Vitality points for using Buddhify, Calm and Headspace</li>
<li>Discounts on Weight Watchers</li>
<li>50%-80% off Comprehensive Private Health screenings</li>
</ul>
Our Culture & Recruitment Process
 At iProov, we're incredibly proud of the culture we've carefully curated. Our culture enables diverse thought, curiosity and innovation. Our team strives to do everything to the highest standard possible to achieve the remarkable. To do that we need different perspectives, experiences and ideas alongside an environment where these are welcomed - we want everyone to feel confident in bringing their full capabilities to work. We firmly believe psychological safety is key to building and nurturing great teams. We’re a small and dynamic company, that means having the right skills is important, and we know that our best work emerges when people feel secure, welcomed and respected.
 As an equal opportunities employer, we encourage applications from people of all backgrounds. We’re committed to building a workforce that is representative of the people we serve. We will not put someone at a disadvantage or treat them less favourably because of race, color, national origin, ancestry, age, disability, creed, religion or belief, sex, sexual orientation, gender reassignment, marriage or civil partnership, or pregnancy and maternity. Our goal is to find people who are passionate about creating a safer, more secure world.
 Our recruitment process is designed to be fair and transparent, focusing solely on your qualifications, competence, and suitability for the role. We review all applications carefully and will be in touch with shortlisted candidates regarding the next steps in our interview process. If you need an adjustment for a disability or any other reason during the hiring process, please send a request to careers@iproov.com

ML Engineer (CoreAI)

<div><div><div>Job ID: R0052537</div>
</div><div><div><div><div><div>Location</div>
<div>London, Middlesex</div>
</div></div></div><div></div><div><div><div><div>Hours/week</div>
<div>37.5 hrs/week</div>
</div></div></div><div></div><div><div><div><div>Payrate range</div>
<div>Unknown</div>
</div></div></div></div><div><div>We believe in better. And we make it happen.
Better content. Better products. And better careers.
Working in Tech, Product or Data at Sky is about building the next and the new. From broadband to broadcast, streaming to mobile, SkyQ to Sky Glass, we never stand still. We optimise and innovate.
We turn big ideas into the products, content and services millions of people love.
And we do it all right here at Sky.
Join us to rethink how sports are experienced. Our AI-driven platform powers immersive, personalised live sports&mdash;giving fans control, fresh perspectives, and predictive insights during the action.
As a Principal Machine Learning Engineer, you&rsquo;ll shape the technical strategy and delivery of production ML systems that transform raw sports data and live video into real-time insights and personalised experiences for millions of fans.
For this role we offer the hybrid working approach with 2 days a week onsite in Osterley office.
What you&rsquo;ll do:
You&rsquo;ll be the technical lead for a critical ML domain (e.g., live sports insights and personalisation, real-time ranking, computer vision for multi-angle video, or streaming inference). Expect to influence roadmaps, architecture, and platform evolution&mdash;not just single models&mdash;while mentoring engineers and data scientists and raising the bar across teams.
<ul><li>Lead the end-to-end development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams.
</li></ul><ul><li>Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded responsible and ethical AI principles from design through deployment.
</li></ul><ul><li>Integrate model driven insights into personalisation engines, tailoring recommendations based on favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data.
</li></ul><ul><li>Define advanced experimental designs, lead A/B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end productionisation from data ingestion through deployment and ongoing model monitoring.
</li></ul><ul><li>Design, architect, and operate low latency, highly reliable cloud based AI systems for live sports scenarios, ensuring resilient performance during peak traffic, responsible model behaviour in real time, and an optimal balance between cost, latency, and production scale performance. 
</li></ul>What you'll bring
<ul><li>Proven extensive lead level engineering experience delivering data&ndash;driven ML systems, with clear ownership of technical direction, mentoring, and delivery.
</li></ul><ul><li>Working knowledge of modern ML techniques, including Generative AI, and how emergent models can extract insights from multimodal sports data (e.g., numerical, spatial, video, or metadata).
</li></ul><ul><li>Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch, TensorFlow), including taking models from experimentation into production model serving.
</li></ul><ul><li>End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries, drift detection, automated retraining, and infrastructure as code practices.
</li></ul><ul><li>Proven technical leadership experience including mentoring and guiding Senior and Mid-Level Data Scientists both in their day-to-day work and career development. Experience of working in a fast-changing environment is vital demonstrating adaptability and ability to support the team through times of uncertainty, pivoting as necessary.
</li></ul>Nice to have
<ul><li>Understanding of sports data, including hands-on experience working with event data, tracking data, or other high-volume sports datasets, and converting these into actionable analytical or predictive insights. 
 
</li></ul><ul><li>Being a Sports Fan &ndash; we immerse ourselves in Sport so having a passion for sport and a desire to push the sports experience to the next level is a real bonus. 
</li></ul>The rewards
There's one thing people can't stop talking about when it comes to #LifeAtSky: the perks. Here&rsquo;s a taster:
<ul><li>Sky Q, for the TV you love all in one place
</li></ul><ul><li>The magic of Sky Glass at an exclusive rate
</li></ul><ul><li>A generous pension package
</li></ul><ul><li>Private healthcare
</li></ul><ul><li>Discounted mobile and broadband
</li></ul><ul><li>A wide range of Sky VIP rewards and experiences 
</li></ul> 
Inclusion &amp; how you'll work
 
We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can.
 
We&rsquo;ve embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You&rsquo;ll find out more about what hybrid working looks like for your role later on in the recruitment process. 
 
Your office space
 
Osterley
 
Our Osterley Campus is a 10-minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers.
 
On campus, you&rsquo;ll find 13 subsidised restaurants, cafes, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon. 

 
We'd love to hear from you
 
Inventive, forward-thinking minds come together to work in Tech, Product and Data at Sky. It&rsquo;s a place where you can explore what if, how far, and what next.
But better doesn&rsquo;t stop at what we do, it&rsquo;s how we do it, too. We embrace each other&rsquo;s differences. We support our community and contribute to a sustainable future for our business and the planet.
If you believe in better, we&rsquo;ll back you all the way.
Just so you know: if your application is successful, we&rsquo;ll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.</div></div></div>

Principal Machine Learning Engineer (Live Sports Insights)

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

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>Location: 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.

The Ads Foundational Representations (AFR) 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.

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:
<ul>
<li>Multimodal &amp; Content Embeddings - 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>Contextual and Behavioral Relevance - 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>Knowledge Graph Embeddings - Building representations for the Knowledge graph entities, e.g., intellectual properties/brands, to be used for high-precision targeting &amp; business insights.</li>
<li>User Intent Modeling - 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>LLM-based Representations - Leveraging LLMs, VLMs, and foundational models to build complex representations of Reddit entities that improve ranking outcomes</li>
</ul>
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.

As a Senior ML Engineer, 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.

Responsibilities
<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>
Required Qualifications:
<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>
Preferred Qualifications:
<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>
Benefits:
<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>
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.

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.

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.</div></div>

Senior Machine Learning Engineer, Ads Foundational Representations

Information Tech Consultants

<div>
 
 
 Job Title:
 
 Data Scientist/Machine Learning Engineer
 
 
 
 Location:
 
 UK
 
 
 
 Experience:
 
 2&ndash;5 years
 
 
 
 Education:
 
 Master's in Science (IT/Computer Science/Engineer)
 
 
 
 Employment Type:
 
 Full-Time
 
 
 
 UK based candidates only.
 
 
 
 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.
 
 
 
 Required Skills:
 
 
 <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>
 
 
 Preferred Skills:
 
 
 <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>
 
 
 
 
 
 Qualifications :
 
 
 <ul>
 <li>
 
 Master&rsquo;s (Required)
 
 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>
 
 
</div>

Ultralytics

<div>
 
 About Ultralytics:
 
 
 
 At Ultralytics, we commit to relentless innovation in the AI space and seek team members who resonate with our ambition to produce the world's best YOLO AI models. If you're obsessed with AI, eager to make an impact on the world and thrive in dynamic, high-intensity environments, we invite you to apply for a position on our team.
 
 
 
 🌎 Location and Legalities
 
 
 
 This full-time LLM Engineer position is based onsite in our brand-new Ultralytics office in London, UK. Applicants must have legal authorization to work in the UK, as Ultralytics does not provide visa sponsorship.
 
 
 
 🚀 What You'll Do
 
 
 
 As an LLM Engineer at Ultralytics, you will spearhead the development and integration of advanced language model capabilities across our ecosystem. You will work on cutting-edge projects that merge the power of Large Language Models (LLMs) with our state-of-the-art computer vision technologies. Key responsibilities include:
 
 
 <ul>
 <li>
 Developing and scaling robust LLM-powered applications using a variety of APIs, including OpenAI, Anthropic, and Gemini.
 </li>
 <li>
 Implementing and managing multi-API workflows using tools like LiteLLM to ensure flexibility and resilience.
 </li>
 <li>
 Building sophisticated Retrieval-Augmented Generation (RAG) systems, leveraging advanced techniques like embeddings with Voyage AI, rerankers, and query enrichment.
 </li>
 <li>
 Designing and maintaining efficient data pipelines and vector storage solutions using MongoDB Atlas Vector Search.
 </li>
 <li>
 Fine-tuning LLMs on custom datasets to enhance performance for specialized tasks related to our documentation and user support.
 </li>
 <li>
 Collaborating with our YOLO development team to explore and build innovative multi-modal solutions.
 </li>
 <li>
 Automating deployment and testing processes using CI/CD pipelines with GitHub Actions.
 
 
 </li>
 </ul>
 Your work will directly enhance the Ultralytics HUB platform and empower our global community of developers and researchers.
 
 
 
 🛠️ Skills And Experience
 
 
 
 <ul>
 <li>
 5+ years of experience in software engineering, with a strong focus on AI and Machine Learning (ML).
 </li>
 <li>
 Expert-level proficiency in Python and deep learning frameworks, particularly PyTorch.
 </li>
 <li>
 Proven experience building and deploying applications with LLM APIs such as OpenAI, Anthropic, Gemini, and DeepSeek.
 </li>
 <li>
 Hands-on experience with the full RAG pipeline, including vector embeddings, rerankers, and data indexing in databases like MongoDB.
 </li>
 <li>
 Practical knowledge of LLM fine-tuning, prompt engineering, and performance optimization.
 </li>
 <li>
 Familiarity with MLOps principles and tools, including CI/CD with GitHub Actions.
 </li>
 <li>
 A strong interest in computer vision and an understanding of object detection models like Ultralytics YOLO11 is a significant plus.
 </li>
 <li>
 Excellent problem-solving skills and the ability to perform in a fast-paced, high-intensity environment.
 
 
 </li>
 </ul>
 
 🌟 Cultural Fit - Intensity Required
 
 
 
 Ultralytics is a high-performance environment for world-class talent obsessed with achieving extraordinary results. We operate at a relentless pace, demanding exceptional dedication and an unwavering commitment to excellence, guided by our mission, vision, and values. Our team thrives on audacious goals and absolute ownership. This is not a conventional workplace. If your priority is predictable comfort or a standard work-life balance over the relentless pursuit of progress, Ultralytics is not for you. We seek driven individuals prepared for the profound personal investment required to make a defining contribution to the future of AI.
 
 
 
 💶 Compensation And Benefits
 
 
 
 <ul>
 <li>
 Competitive Salary: Highly competitive based on experience.
 </li>
 <li>
 Startup Equity: Participate directly in our company's growth and success.
 </li>
 <li>
 Hybrid Flexibility: 3 days per week in our brand-new office - 2 days remote.
 </li>
 <li>
 Generous Time Off: 24 days vacation, your birthday off, plus local holidays.
 </li>
 <li>
 Flexible Hours: Tailor your working hours to suit your productivity.
 </li>
 <li>
 Tech: Engage with cutting-edge AI projects and contribute to leading open-source software.
 </li>
 <li>
 Gear: Brand-new Apple MacBook and Apple Display provided.
 </li>
 <li>
 Team: Become part of a supportive and passionate team environment.
 
 
 </li>
 </ul>
 
 What we offer:
 
 
 
 
 Cutting-Edge-next generation AI computer vision technology:
 
 contribute to building cutting edge computer vision AI models based on the YOLO framework.
 
 
 
 Impactful Work:
 
 Shape the future of AI-powered solutions that transform industries.
 
 
 
 Collaborative Culture:
 
 Join a talented and passionate team that values open communication and innovation.
 
 
 
 Ultralytics Handbook
 
 
 
 Comprehensive guide to our company&rsquo;s mission, vision, values, and operational practices. This handbook is designed to provide key insights and resources for our (future) team members, collaborators, and community to align with Ultralytics' core principles.
 
 
 Link: https://handbook.ultralytics.com/
 
 
 
 Ultralytics is an equal opportunity employer and are committed to building an inclusive workplace. We believe that everyone should be able to bring their whole selves to work, and we do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability or any other legally protected status.
 
 
 
</div>

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