▷ 15h Left: AI Trainer for Norwegian Writers/Speakers(College Degree Required)

Alignerr
Newcastle upon Tyne
3 weeks ago
Applications closed

Alignerr.com is a community of subject matter expertsfrom several disciplines who align AI models by creatinghigh-quality data in their field of expertise to build the futureof Generative AI. Alignerr is operated by Labelbox. Labelbox is theleading data-centric AI platform for building intelligentapplications. Teams looking to capitalize on the latest advances ingenerative AI and LLMs use the Labelbox platform to inject thesesystems with the right degree of human supervision and automation.Whether they are building AI products by using LLMs that requirehuman fine-tuning, or applying AI to reduce the time associatedwith manually-intensive tasks like data labeling or findingbusiness insights, Labelbox enables teams to do so effectively andquickly. Current Labelbox customers are transforming industrieswithin insurance, retail, manufacturing/robotics, healthcare, andbeyond. Our platform is used by Fortune 500 enterprises includingWalmart, Procter & Gamble, Genentech, and Adobe, as well ashundreds of leading AI teams. We are backed by leading investorsincluding SoftBank, Andreessen Horowitz, B Capital, GradientVentures (Google's AI-focused fund), Databricks Ventures, SnowpointVentures and Kleiner Perkins. About the Role Shape the future of AIin the Norwegian language. This innovative role as an AI Trainer -Norwegian Writers, offers a unique opportunity to leverage yoursubject-matter expertise and develop your AI skills. You will playa pivotal role in training AI models, ensuring the accuracy andrelevance of Norwegian content generated by AI. This positionallows for flexible scheduling, and your contributions willdirectly impact the advancement of AI in the Norwegian language.Your Day to Day - Educate AI: Analyze and provide feedback onAI-generated outputs related to the Norwegian language. Yourguidance will directly improve the AI's accuracy and ability toapply its knowledge to real-world problems. - Problem Solving:Using your expertise, you will provide step-by-step solutions andexplanations to complex problems in Norwegian. This could includechecking punctuation, spelling and grammar, and/or creativewriting. Your input will be crucial in teaching the AI how toreason through these problems effectively. - Red Teaming: Utilizeyour deep understanding of the field to identify potential biases,limitations, or inaccuracies in the AI's knowledge base. Design andconduct tests that push the boundaries of the model'sunderstanding, ensuring its outputs are reliable and applicable toreal-world scenarios. - You create your own working hours dependingon project length. About You - Enrolled in or have completed anAssociates’ degree or higher from an accredited institution. -Fluent proficiency in the Norwegian language. - Possess a strongwriting style with excellent English-language spelling and grammarskills. - Have a critical eye and the ability to clearly articulatethe strengths and weaknesses of written text. - Professionalwriting experience as a researcher, journalist, technical writer,editor, or similar roles - Interest in AI and machine learningconcepts Important Information This is a freelance positioncompensated on an hourly basis. Please note that this is not aninternship opportunity. Candidates must be authorized to work intheir country of residence, and we do not offer sponsorship forthis 1099 contract role. International students on a valid visa maybe eligible to apply; however, specific circumstances should bediscussed with a tax or immigration advisor. We are unable toprovide employment documentation at this time. Compensation ratesmay vary for non-US locations. Labelbox strives to ensure payparity across the organization and discuss compensationtransparently. The expected hourly rate range for UnitedStates-based candidatesis below. Exact compensation varies based ona variety of factors, including skills and competencies,experience, and geographical location. Pay Range (rate per hour)$15—$150 USD

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Portfolio Projects That Get You Hired for Machine Learning Jobs (With Real GitHub Examples)

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!

Jobs Careers

Machine Learning Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.

Jobs

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.

🍪 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.