Legal Onboarding Specialist

London
2 weeks ago
Applications closed

Related Jobs

View all jobs

AI Product Manager – Legal only

HR Data Analyst

eDiscovery Litigation Data Analyst (Remote)

Patent Attorney, AI and Machine Learning - UK based

Media Data Analyst

Senior Data Engineer - Databricks

Legal Onboarding Specialist
A brilliant opportunity for a talented corporate law paralegal or contract law specialist, to work as a Legal Onboarding Specialist, joining a market-leading disruptive software technology firm in London. Offering excellent training, career progression and prospects, this is a unique opportunity to work for a rapidly expanding machine learning software house. This opportunity involves onboarding and implementing legal AI technology to support seamless integration into legal teams’ current contract management processes.
Location: Central London– 3 days in office / 2 days remote
Salary: £30,000 - £40,000 per annum + healthcare, pension etc.
Requirements for Legal Onboarding Specialist

  • Experienced specifically in contract negotiation
  • At least 1 year of commercial legal experience in contract law or corporate law (i.e. paralegal in-house or in a private practice in a corporate department)
  • Degree educated, ideally with a 2.1 or 1st class Law degree
  • At least AAB at A Level or equivalent UCAS points
  • Ability to understand legal contracts, negotiation positions and processes
  • You are driven, pro-active with outstanding attention to detail
  • You have incredible focus and can work with efficiency and speed
  • Exceptional written communication skills with fluent spoken and written English
    Responsibilities for Legal Onboarding Specialist
    You will work for a Legal-tech software house, supporting clients in their onboarding phase including:
  • Work with a diverse client base of in-house teams, playing a central role in ensuring customer success from the outset through collaboration during the onboarding process.
  • Work closely with the Customer Success Manager to onboard and implement legal AI technology into client sites.
  • Support seamless integration of the technology into customers’ existing contract management processes.
    What this offers
  • The chance to combine your legal knowledge with the future of technology
  • Working for an industry-leading software company who have a fantastic track record of amazing progression opportunities and rewarding hard work
    Applications
  • If you meet the above criteria we would love to hear from you. Please send an up-to-date CV via the relevant link.
  • We’re committed to creating an inclusive and accessible recruitment process. If you require reasonable adjustments for your application or during the review process, please highlight this by emailing (if this email address has been removed by the job-board, full details for contact are available on our website).
    Keywords: Paralegal / Corporate Law / Contract Law / Legal / Law / Data Entry Specialist / Data Entry Clerk / Data Quality Analyst / Records Management Analyst / Data Administrator / Data Coordinator / Data Operations Analyst / Data Entry Operator / Data Input Clerk / Administrative Assistant (Data Entry) / Typist / Data Entry Associate / Records Clerk / Office Clerk (Data Entry) / Data Processing Assistant / Keyboard Operator / Information Entry Specialist / Graduate / Junior / Trainee / Data Input Specialist / Data Input Operator / Data Input Clerk / Data Input Coordinator / Contract Templater / Data Input Analyst
    ********************************************************************************
    RedTech Recruitment Ltd focus on finding roles for people in science and technology. Even if the above role isn’t of interest, please visit our website to see our other opportunities.
    We are an equal opportunity employer and value diversity at RedTech. We do not discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status

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.

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!

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.

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.