National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Software Engineer - ML Apps (Mining & Text Intelligence) (Remote - United Kingdom)

Yelp
Edinburgh
4 months ago
Applications closed

Related Jobs

View all jobs

Software Manager

Software Engineer III - Data Engineer - Python, SQL - Senior Associate

Software Engineer II - Data Engineer, Python, SQL - Associate

Senior Software Engineer – API & ML Infrastructure

Junior Embedded Software Engineer

Lead Python Software Engineer

JOB DESCRIPTION

Summary

Yelp engineering culture is driven by our : we’re a cooperative team that values individual authenticity and encourages creative solutions to problems. All new engineers deploy working code their first week, and we strive to broaden individual impact with support from managers, mentors, and teams. At the end of the day, we’re all about helping our users, growing as engineers, and having fun in a collaborative environment.

At Yelp, we connect people with great local businesses. We have millions of users sending us hundreds of millions of photos, videos and reviews. But have you ever wondered how we organize those reviews and photos and the insights we derive from them into data products? That’s where the core content group and mining and text intelligence team comes in.

We're looking for experienced engineers who are eager to learn and contribute to building applications using generative AI. You'll have the opportunity to work with large scale visual and textual data sets to build impactful user-facing products and features utilising the latest LLMs and ML models. You will also be responsible for the productionisation and deployment building data pipelines or ETLs to create new online and offline data products. Join us in leveraging machine learning across Yelp to create visual, textual and multi-modal models to offer new products based on our unique content. If you are enthusiastic about learning, eager to take on new challenges, and passionate about creating new ML products, we want you on our team!

This opportunity requires you to be located in the United Kingdom. We’d love to have you apply, even if you don’t feel you meet every single requirement in this posting. At Yelp, we’re looking for great people, not just those who simply check off all the boxes.


What you'll do:

Define problems and gather requirements in collaboration with product managers, teammates and engineering managers. Collect and curate datasets necessary to evaluate and feed the generative models. Develop and validate results of the generative AI models. Fine tune models when necessary. Productionize models for offline and / or online usage. Learn the fine art of balancing scale, latency and availability depending on the problem.


What it takes to succeed:

Good coding skills in Python or equivalent (ideally Java or C++). Hands-on experience in open-ended and ambiguous data analysis (pattern and insight extraction through statistical analysis, data segmentation etc). A craving to learn and use cutting edge AI technologies. Understanding of building data pipelines to train and deploy machine learning models and/or ETL pipelines for metrics and analytics or product feature use cases. Experience in building and deploying live software services in production. Exposure to some of the following technologies (or equivalent): Apache Spark, AWS Redshift, AWS S3, Cassandra (and other NoSQL systems), AWS Athena, Apache Kafka, Apache Flink, AWS and service oriented architecture.


What you'll get:

Full responsibility for projects from day one, a collaborative team, and a dynamic work environment. Competitive salary, a pension scheme, and an optional employee stock purchase plan. 25 days paid holiday (rising to 29 with service), plus one floating holiday. £150 monthly reimbursement to help cover remote working expenses. £81 caregiver reimbursement to support dependent care for families. Private health insurance, including dental and vision. Flexible working hours and meeting-free Wednesdays. Regular 3-day Hackathons, bi-weekly learning groups, and productivity spending to support and encourage your career growth.  Opportunities to participate in digital events and conferences. £81 per month to use toward qualifying wellness expenses. Quarterly team offsites.


Closing

National AI Awards 2025

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Return-to-Work Pathways: Relaunch Your Machine Learning Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like starting from scratch—especially in a specialist field like machine learning. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s machine learning sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve developed, pairing you with mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for machine learning talent in the UK Leverage your organisational, communication and analytical skills in ML contexts Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to machine learning Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to ML Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as an ML engineer, research scientist, MLOps specialist or data scientist with an ML focus, this article will map out the steps and resources you need to reignite your machine learning career.

LinkedIn Profile Checklist for Machine Learning Jobs: 10 Tweaks to Drive Recruiter Interest

The machine learning landscape is rapidly evolving, with demand soaring for experts in modelling, algorithm tuning and data-driven insights. Recruiters hunt for candidates proficient in Python, TensorFlow, PyTorch and MLOps processes. A generic profile simply won’t cut it. Our step-by-step LinkedIn for machine learning jobs checklist covers 10 targeted tweaks to ensure your profile ranks in searches and communicates your technical impact. Whether launching your ML career or seeking leadership roles, these optimisations will sharpen your professional narrative and boost recruiter engagement.

Part-Time Study Routes That Lead to Machine Learning Jobs: Evening Courses, Bootcamps & Online Masters

Machine learning—a subset of artificial intelligence—enables computers to learn from data and improve over time without explicit programming. From predictive maintenance in manufacturing to recommendation engines in e-commerce and diagnostic tools in healthcare, machine learning (ML) underpins many of today’s most innovative applications. In the UK, demand for ML professionals—engineers, data scientists, research scientists and ML operations specialists—is growing rapidly, with roles projected to increase by over 50% in the next five years. However, many aspiring ML practitioners cannot step away from work or personal commitments for full-time study. Thankfully, a rich ecosystem of part-time learning pathways—Evening Courses, Intensive Bootcamps and Flexible Online Master’s Programmes—empowers you to learn machine learning while working. This comprehensive guide examines each route: foundational CPD units, immersive bootcamps, accredited online MSc programmes, funding options, planning strategies and a real-world case study. Whether you’re a software developer branching into ML, a statistician aiming to upskill, or a professional exploring AI-driven innovation, you’ll discover how to build in-demand ML expertise on your own schedule.