Sr. AI/ML Solution Architect UK (Pre-sale engineer)

ArangoDB
1 year ago
Applications closed

Sr. Solution Architect - UK About ArangoDB Founded in Germany and now headquartered in San Francisco, ArangoDB is the most highly scalable, open-source, Graph Database with AI/ML capabilities available in the market. In addition to graphs, it is natively supporting a number of data models including Document, and Key-Value as well as Full-Text Search and Retrieval. It serves as the scalable backbone for Graph-Analytics and complex data architectures across many different industries. Developers can build high-performance applications using a convenient SQL-like query language or JavaScript extensions. Find out more at the Company page and follow us on Linkedin . As a Data Science Solution Architect at ArangoDB, you are both a pre-sales technical consultant and a product evangelist. Through product presentations, Proof of Concepts, and community engagement, you demonstrate to clients the technical problem-solving abilities of our Data Science suite as well as core capabilities and discuss use cases directly with data scientists, developers, ML ops teams, and managers on different levels.   Location: UK Only candidates in the UK will be considered for the position. While this is a work-from-home role, some travel to client locations may be required.   You Will: Craft and deliver outstanding technical presentations and architecturally sound demonstrations of ArangoDB and its Data Science suite for clients. Drive Proof of Concepts/Technology (PoCs/PoTs) with prospects and customers, often in comparison to other (NoSQL) database technologies and other Machine Learning/AI enterprise solutions. Solve technical problems of our (potential) clients with the best solution for the client in mind. Work closely with the Sales Executives in the US and Europe, participating in client meetings. Evangelize ArangoDB’s Data Science suite to prospects and potentially in 3rd party presentations and panel discussion designed to generate awareness. Coordinate with Product Management and Marketing by providing them with detailed feedback regarding customer environment,  demands, and trends. Work with Marketing for contributions and feedback on technical whitepapers, conduct seminars, assist with trade shows and other marketing-related events in this area Communicate with and contribute to the worldwide ArangoDB community. Other duties as assigned from time to time.   Your Skills: 5+ years of experience in a technical sales or consulting capacity with enterprises, focusing on complex solution sales of mission-critical data systems (databases, data warehouses, big data systems, analytics, and machine learning)  Deep technical understanding of data and ML tooling, workflows, and trends in enterprise setting Proficiency in Python, Spark, and/or SQL with experience developing ETL applications You have a broad and thorough knowledge of systems and application design as well as in-depth knowledge of (NoSQL) databases and distributed systems. You are a high-energy, upbeat, tenacious team player with outstanding interpersonal skills and you have the ability to persuade others through presentations, demonstrations, and written communication. Others would describe you as a Self-starter, perpetual learner, team player, and relationship builder. Bachelor's degree in Computer Science or relevant experience  Working knowledge of  Neural Networks, ML tasks like Node Classification, Node Similarity, Link Prediction, and related concepts. You are fluent in English both verbal and written.   Extra points for: Previous experience with Graph databases or frameworks Experience building and integrating LLMs Knowledge of infrastructure stacks (AWS, Linux, Scala, Docker, Kubernetes, Kafka, Spark, etc.) Administration experience with various operating systems (Linux, Windows), distributed systems, cloud, and data storage   Why Join ArangoDB Our headquarters is in San Francisco (US) and we have an office in Cologne (Germany), but most of our diverse team works remotely worldwide. So, do you prefer your desk at home or do you want to join us at one of our locations? Your choice. The ArangoDB team comes from 5 different continents and more than 20 countries. Diverse backgrounds enable us to see new solutions. We invite people from every culture, national origin, religion, sexual orientation, gender identity or expression, and of every age to apply to our positions. All employment decisions are based on business needs, job requirements, and individual qualifications. Arango is committed to a workplace free of discrimination and harassment based on any of these characteristics. We love this diversity and encourage everyone curious and visionary to join the multi-model movement. Powered by JazzHR

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.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.