AI / Machine Learning Engineer (Remote)

vidIQ
London
9 months ago
Applications closed

Related Jobs

View all jobs

AI/ Machine Learning Engineer NLP / LLM - Contract

Lead AI & Machine Learning Engineer

Lead Software Engineer - Agentic AI/Machine Learning

Remote ML Engineer (NLP/LLM): Build Next-Gen AI

Junior Machine Learning Engineer

Staff Machine Learning Engineer

About vidIQ

vidIQ builds software to help YouTube creators achieve their goals. Our mission is to advance the creator's journey with actionable data-driven insights and AI-powered tools. We are dedicated to our values of being creator-obsessed, lean and fast, and scientific. Having already supported millions of creators, we invite stunning new co-workers to join us in reaching millions more.

Imagine a product that reached over a million users without a traditional sales team. This product stands at the forefront of career evolution, where everyone can be their own brand with unlimited growth potential. That's the opportunity at vidIQ—an infinite market, a large and highly engaged customer base, and the chance to help scale the platform that delivers insights to millions of creators.

Discover more about vidIQ firsthand atwww.vidiq.com.

About the Team

We're a team of 100+ people and growing quickly. Our vision is to be the smart copilot for every creator. We strive to create a welcoming environment where our team of smart, passionate people can share ideas with each other and do their best work. We are looking for team members who are excellent at their craft, communicate with kindness, and act like owners.

An overview of our technology stack

  • Frontend: Typescript, React.js, Next.js

  • Backend: Scala/Python/Node.js

  • Infrastructure & CI/CD: Kubernetes, Docker, GitHub, ArgoCD

  • Cloud: AWS, GCP, Azure

  • Databases: PostgreSQL, MongoDB, DynamoDB, OpenSearch

  • Data processing: Python, Spark, Kafka, Airflow, Pandas, Numpy

  • ML libraries: PyTorch, Hugging Face, sci-kit-learn, Tensorflow, Keras

  • ML algorithms: multi-modal LLMs, Diffusion Models, Recommender Systems, ANN


About the Role

We are looking for a highly-motivatedAI / Machine Learning Engineer, with a background in backend development. In this role, you'll work closely with a cross-functional team to drive product innovation and deliver high-impact results. The ideal candidate will have robust engineering experience, a proactive mindset, and a proven track record in product development. You will be expected to collaborate with key stakeholders, articulate technical concepts to non-technical audiences, and lead by example in a fast-paced, results-oriented environment.

What you will be doing 

  • Work closely with Product Managers to frame problems within business context and deliver the highest impact to our users

  • Design, implement and ship new features with a high level of responsibility and ownership

  • Implement scalable solutions to consistently serve a vast global user base

  • Help establish architecture based on technology and our needs

  • Build, train and test Machine learning solutions focusing on natural language processing, recommender systems, computer vision

  • Write well-crafted, well-tested, maintainable code to convert our ML models into working pipelines

  • Collaborate closely with Frontend, DevOps, and Data Engineering teams to deliver cohesive end-to-end solutions, align on technical decisions, and ensure smooth integration between system components

  • Participate in code-reviews to ensure code quality and distribute knowledge

  • Monitor and troubleshoot existing features and resolve any issues that arise



Requirements

  • 5+ yearsof professionalsoftware engineering experience(preferably in Python)

  • 2+ yearsof experiencedeveloping and delivering ML solutionsinto production

  • Hands-on experiencebuilding and optimizing end-to-end data and machine learning pipelines, with a focus onLLM-based solutions

  • Engineering mindset, with a high degree of comfort in designing software and producing production-grade code

  • Proactive, results-oriented self-starterwith a proven ability to drive growth and innovation in dynamic environments.

  • Ability to work with modern data integration and analytics tools

  • Experience with AI-dev tools (e.g. GitHub Co-Pilot, Cursor)

  • Ability to turn ML paper into working code

Nice to have 

  • B.S., M.S. or PhD in Computer Science or related technical field

  • Developer-level experience with Kubernetes and Docker

  • Experience with data processing technologies (e.g. Spark, Kafka, Airflow)

  • Experience working with RDBMS and NoSQL data scores (PostgreSQL, DynamoDB and alike)

  • Experience in product management

Perks and Benefits

  • Work Remotely:Embrace the freedom to choose your ideal workspace anywhere in the world.

  • Flexible Time Off:We support a flexible vacation policy allowing you to take time off when you need to recharge.

  • Communication Stipend:Enjoy a monthly stipend to cover your phone and internet expenses, helping you stay connected effortlessly.

  • Global Impact:Join our diverse team that’s shaping the future of the creator economy across the globe.

  • Competitive Compensation:vidIQ believes in offering competitive compensation that reflects your skills, experience, and contributions. We ensure fairness through internal equity and geo-location based pay, with the upper range reserved for individuals demonstrating exceptional job knowledge and skills.

Our Commitment

At vidIQ, we dedicate ourselves to enabling creators of all kinds to succeed. We prioritize attracting diverse talent and fostering an environment that encourages collaboration, creativity, and personal growth. We are committed to building a company and a community where individuals thrive by being true to themselves and are inspired to do their best work every day.

If you share our enthusiasm for empowering creators, we would love to hear from you. Click the“Apply”button below to start your journey with us.

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.

Jobs

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

Education Jobs

Maths for Machine Learning Jobs: The Only Topics You Actually Need (& How to Learn Them)

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.

Jobs

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.