Senior Software Engineer, Machine Learning

Lawhive
London
1 month ago
Applications closed

Related Jobs

View all jobs

Senior Software Engineer

Senior Software Engineer - Search Quality (Remote - United Kingdom)

Senior Software Engineer (GO/PHP)

Senior Software Engineer - AI (Basé à London)

SENIOR SOFTWARE ENGINEER: UNITY (Basé à London)

Senior Software Engineer in Product

We’re on a mission to make sureeveryone has access to the law.

Lawhive is an online platform for consumers and small businesses to get legal help for a fraction of the cost of a law firm. Our platform combines regulated human lawyers collaborating alongside the world’s first AI lawyer specifically built for consumer legal work.

Equal access to the law is one of the biggest and most pressing unsolved problems in society today. We’re passionate about leveling the playing field and believe access to the law should be a basic utility in society.

Our AI lawyer Lawrence is built on top of our own fine-tuned LLM who has passed the Solicitors Qualifying Exams (SQE).

We have backing from leading US and UK VC funds including Google Ventures, Balderton Capital and TQ Ventures (who have funded 82 unicorns between them!). We recently secured a $40m Series A funding round to facilitate international expansion and to grow our team. This represents one of the five largest Series A rounds in Europe for 2024!

The Role

We’re looking for a Senior Software Engineer / ML to join our AI team to bring our our latest AI-driven features and services into production. Deploying them at scale, improving infrastructure, and ensuring robustness in production. You’ll work closely with AI researchers, software engineers, and product teams to bridge the gap between cutting-edge AI research and real-world applications.

Responsibilities

  • Developing production-readyAPIs and servicesthat expose AI functionality to internal and external applications.
  • Improving reliability & monitoringfor AI-driven applications in production.
  • Scaling AI systems to handle real-world legal use cases(e.g., legal document analysis, case predictions, automated legal advice).
  • Collaborating with AI engineersto ensure smooth deployment of AI workflows and models into production.
  • Working with event-driven architecturesand async workflows to process large-scale AI workloads efficiently.
  • Ensuring security & compliancein AI-driven legal services.

Our Engineering Culture

  • Ship daily -We’re building and releasing features fast, going from idea to production in hours rather than weeks.
  • Empathise with users- Lawyers and legal clients have unique perspectives, preferences and expectations. We build products which understand them deeply.
  • Strive for excellence- We’re ambitious and moving fast. The whole business is pushing to be a category defining legal tech company.
  • Constantly learning and experimenting- We’re at the cutting edge of using AI to directly improve people’s lives. We take a blue-sky but pragmatic approach to how we apply new technologies.

Our Tech Stack

  • TypeScript (Full-stack)
  • React + Next.js, Tailwind, Prisma, tRPC
  • PostgreSQL, MongoDB, Redis
  • Serverless, AWS, Google Cloud, Github Actions
  • DBT, BigQuery
  • Terraform
  • Python

Requirements

  • Strong Python experiencein building scalable backend systems.
  • Familiarity with API design & distributed systems architecture.
  • Experience working with event-driven architectures(e.g. Kafka, Pub/Sub, AWS Step Functions, etc.).
  • Comfortable optimising performance & scaling distributed AI workloads.
  • Experience working with cloud platforms (AWS, GCP etc).
  • Understanding of best practices in observability, monitoring, and debugging.

Nice to Have

  • Experience deploying machine learning models to production(ML Ops experience a plus).
  • Experience withVector DatabasesandAI Model Serving

Benefits

  • ✈️ 34 Holidays (25 days annual leave + your birthday off + bank hols in England)
  •  Equity
  •  Pension
  • ⛳️ Regular team building activities, socials, and annual retreat!
  • 20% off legal fees through Lawhive

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.

Contract vs Permanent Machine Learning Jobs: Which Pays Better in 2025?

Machine learning (ML) has swiftly become one of the most transformative forces in the UK technology landscape. From conversational AI and autonomous vehicles to fraud detection and personalised recommendations, ML algorithms are reshaping how organisations operate and how consumers experience products and services. In response, job opportunities in machine learning—including roles in data science, MLOps, natural language processing (NLP), computer vision, and more—have risen dramatically. Yet, as the demand for ML expertise booms, professionals face a pivotal choice about how they want to work. Some choose day‑rate contracting, leveraging short-term projects for potentially higher immediate pay. Others embrace fixed-term contract (FTC) roles for mid-range stability, or permanent positions for comprehensive benefits and a well-defined career path. In this article, we will explore these different employment models, highlighting the pros and cons of each, offering sample take‑home pay scenarios, and providing insights into which path might pay better in 2025. Whether you’re a new graduate with a machine learning degree or an experienced practitioner pivoting into an ML-heavy role, understanding these options is key to making informed career decisions.

Machine‑Learning Jobs for Non‑Technical Professionals: Where Do You Fit In?

The Model Needs More Than Math When ChatGPT went viral and London start‑ups raised seed rounds around “foundation models,” many professionals asked, “Do I need to learn PyTorch to work in machine learning?” The answer is no. According to the Turing Institute’s UK ML Industry Survey 2024, 39 % of advertised ML roles focus on strategy, compliance, product or operations rather than writing code. As models move from proof‑of‑concept to production, demand surges for specialists who translate algorithms into business value, manage risk and drive adoption. This guide reveals the fastest‑growing non‑coding ML roles, the transferable skills you may already have, real transition stories and a 90‑day action plan—no gradient descent necessary.

Quantexa Machine‑Learning Jobs in 2025: Your Complete UK Guide to Joining the Decision‑Intelligence Revolution

Money‑laundering rings, sanctioned entities, synthetic identities—complex risks hide in plain sight inside data. Quantexa, a London‑born scale‑up now valued at US $2.2 bn (Series F, August 2024), solves that problem with contextual decision‑intelligence (DI): graph analytics, entity resolution and machine learning stitched into a single platform. Banks, insurers, telecoms and governments from HSBC to HMRC use Quantexa to spot fraud, combat financial crime and optimise customer engagement. With the launch of Quantexa AI Studio in February 2025—bringing generative AI co‑pilots and large‑scale Graph Neural Networks (GNNs) to the platform—the company is hiring at record pace. The Quantexa careers portal lists 450+ open roles worldwide, over 220 in the UK across data science, software engineering, ML Ops and client delivery. Whether you are a graduate data scientist fluent in Python, a Scala veteran who loves Spark or a solutions architect who can turn messy data into knowledge graphs, this guide explains how to land a Quantexa machine‑learning job in 2025.