Senior Software Engineer - Reasoning Infrastructure

London

1 year ago

Applications closed

Related Jobs

View all jobs

Senior Machine Learning Engineer

Lead Data Engineer

Data Science Practitioner

Senior Data Engineer

Senior Machine Learning Scientist

Full Stack Data Engineer

Senior Software Engineer - Reasoning Infrastructure

The Mission
Proactive Global have partnered with an exciting AI business who are striving to create the world's
leading, commercially scalable, safe, and advanced humanoid robots that seamlessly integrate into
daily life and amplify human capacity.

Vision
In a world where artificial intelligence opens up new horizons, our faith in its potential unveils a new
outlook where, together, humans and machines build a new future filled with knowledge,
inspiration, and incredible discoveries. The development of a functional humanoid robot underpins
an era of abundance and well-being where poverty will disappear, and people will be able to choose
what they want to do. We believe that providing a universal basic income will eventually be a true
evolution of our civilization.

Solution
As the demands on our built environment rise, labour shortages loom. With the world's workforce
increasingly moving away from undesirable tasks, the manufacturing, construction, and logistics
industries critical to our daily lives are left exposed. By deploying our general-purpose humanoid
robots in environments deemed hazardous or monotonous, we envision a future where human wellbeing
is safeguarded while closing the gaps in critical global labour needs.

Position Overview:
As a Software Engineer in the Robotic Reasoning team, you will spearhead the development and
optimization of RAG pipelines and integrations for our AI-driven solutions, utilizing LLMs, RAGs and
other cutting-edge technologies in NLP and Machine Learning.

Responsibilities:
Design and implement robust RAG pipelines to ensure planning and memory capabilities for our
robots.
Integrate and maintain LLM based solutions, different types of DBs, and various types of sensorial
inputs within our systems.
Enhance data flow and system integrations within a modular architecture to support advanced data
processing and information retrieval
Build and maintain logging and monitoring subsystems.

Requirements:

Advanced degree in Computer Science, Data Engineering, AI or related field.
Extensive experience in RAG pipeline frameworks and orchestration tools (LlamaIndex, LangChain, Spark, Kafka, Airflow).
Demonstrated ability with Python and various DBs (MongoDB, Pinecone, Elasticsearch, Pgvector, Neo4j).
Strong background in LLM-as-a-service and Cloud Technologies (Open AI, AWS, Google Cloud, Azure).
Experience with Machine Learning and Deep Learning technologies.
Experience in Semantic Mapping and Simulation environments.
Knowledge of ROS.

Proactive Global is committed to equality in the workplace and is an equal opportunity employer.
Proactive Global is acting as an Employment Business in relation to this vacancy

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

Industry Insights

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

Feb 3, 2026

Jobs

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.

Jan 29, 2026

Careers Jobs

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.

Jan 24, 2026

Education

The Skills Gap in Machine Learning Jobs: What Universities Aren’t Teaching

Machine learning has moved from academic research into the core of modern business. From recommendation engines and fraud detection to medical imaging, autonomous systems and language models, machine learning now underpins many of the UK’s most critical technologies. Universities have responded quickly. Machine learning modules are now standard in computer science degrees, specialist MSc programmes have proliferated, and online courses promise to fast-track careers in the field. And yet, despite this growth in education, UK employers consistently report the same problem: Many candidates with machine learning qualifications are not job-ready. Roles remain open for months. Interview processes filter out large numbers of applicants. Graduates with strong theoretical knowledge struggle when faced with practical tasks. The issue is not intelligence or effort. It is a persistent skills gap between university-level machine learning education and real-world machine learning jobs. This article explores that gap in depth: what universities teach well, what they routinely miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in machine learning.