National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Full Stack Software Engineer - Healthcare

Princeton Biopartners
united kingdom, united kingdom
4 months ago
Applications closed

Related Jobs

View all jobs

Machine Learning Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer (Maximo)

Senior Software Engineer – API & ML Infrastructure

Job Title:Full Stack Software Engineer - Healthcare


Industry:Biotechnology Research


Location:UK (Remote)


Princeton Biopartners is a best-in-class provider of integrated consulting solutions to the life sciences sector. Our mission is to improve the evidence base, accessibility, and dissemination of biomedical innovations through strategic advisory, software, and our venture fund. We pride ourselves on establishing long-term client relationships and are dedicated to addressing pain points via integrated and transformative projects. We are looking for a highly motivated and talented Full Stack Software Engineer to become our first full-time technology hire. 


As a Software Engineer, you will be critical in bridging the gap between strategy and implementation. You'll be integral in project execution that combines our strategic insights with tech-forward solutions, ensuring clients receive end-to-end products. You will be expected to bring intellectual curiosity, analytical rigor, creativity, and strategic thinking to every engagement.This is a cross-functional role, with high growth potential - the ideal candidate will be highly driven and relish the chance to wear multiple hats (Engineering, Product, Data).

 

Must Haves:

  • UK based:role is remote, but only open to candidates localized within the UK
  • STEM degree:from a top research-intensive university, preferably in London or Oxbridge
  • Engineering mindset:obsessed with building robust software aligned with best practices
  • Comfortable client facing:as needed to gather requirements and feedback
  • Product-minded:high degree of ownership and deeply invested in the user experience
  • Highly curious:comfortable working through ambiguity with analytical rigor
  • Independent:self-starter, growth mindset, comfortable with limited supervision
  • Efficient:value pragmatism over idealism (efficiently arrive at 80-20 solutions)
  • Structured:thinker, problem solver, and communicator 


Key Responsibilities:

  • Design, develop, and maintain Web, Front End, and Data Visualization applications
  • Produce performant, well tested code that scales gracefully with more features, users, and data
  • Assist with deploying and embedding software products into consulting solutions
  • Understand the trade-offs between different engineering solutions
  • Write and maintain clear, concise documentation 


Technical Expertise: 

  • Previous experience in software engineering, preferably within the Life Sciences Sector
  • Strong grasp of computer science fundamentals: data structures and algorithms, complexity, object oriented design
  • Mastery of modern web technologies & Javascript is essential: React, CSS, Node, Angular, etc.
  • Proficient in at least one all purpose imperative language: Python (ideal), Java, C++, etc.
  • Familiar with modern DevOps / CloudOps best practices - test driven development, CI/CD, etc.  
  • Desirable: prior experience with Azure and NoSQL
  • Desirable: experience and interest in machine learning, data engineering, and data visualization

 

Cultural Fit:

  • Represent the firm in a professional manner and uphold its values and culture in all interactions
  • Entrepreneurial spirit & strong work ethic, demonstrating a drive to pursue new growth opportunities and lead strategic initiatives
  • Ensure confidentiality, honesty, transparency, and integrity in all business dealings while fostering a positive working environment of knowledge sharing, effective collaboration, and mutual support


Benefits:

  • Competitive compensation commensurate with experience
  • Unlimited annual leave 
  • Up to 15% performance-based bonus
  • Flexible working conditions and international travel
  • Budget for co-working space 
  • Professional development programs


We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.

National AI Awards 2025

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.

Return-to-Work Pathways: Relaunch Your Machine Learning Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like starting from scratch—especially in a specialist field like machine learning. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s machine learning sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve developed, pairing you with mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for machine learning talent in the UK Leverage your organisational, communication and analytical skills in ML contexts Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to machine learning Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to ML Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as an ML engineer, research scientist, MLOps specialist or data scientist with an ML focus, this article will map out the steps and resources you need to reignite your machine learning career.

LinkedIn Profile Checklist for Machine Learning Jobs: 10 Tweaks to Drive Recruiter Interest

The machine learning landscape is rapidly evolving, with demand soaring for experts in modelling, algorithm tuning and data-driven insights. Recruiters hunt for candidates proficient in Python, TensorFlow, PyTorch and MLOps processes. A generic profile simply won’t cut it. Our step-by-step LinkedIn for machine learning jobs checklist covers 10 targeted tweaks to ensure your profile ranks in searches and communicates your technical impact. Whether launching your ML career or seeking leadership roles, these optimisations will sharpen your professional narrative and boost recruiter engagement.

Part-Time Study Routes That Lead to Machine Learning Jobs: Evening Courses, Bootcamps & Online Masters

Machine learning—a subset of artificial intelligence—enables computers to learn from data and improve over time without explicit programming. From predictive maintenance in manufacturing to recommendation engines in e-commerce and diagnostic tools in healthcare, machine learning (ML) underpins many of today’s most innovative applications. In the UK, demand for ML professionals—engineers, data scientists, research scientists and ML operations specialists—is growing rapidly, with roles projected to increase by over 50% in the next five years. However, many aspiring ML practitioners cannot step away from work or personal commitments for full-time study. Thankfully, a rich ecosystem of part-time learning pathways—Evening Courses, Intensive Bootcamps and Flexible Online Master’s Programmes—empowers you to learn machine learning while working. This comprehensive guide examines each route: foundational CPD units, immersive bootcamps, accredited online MSc programmes, funding options, planning strategies and a real-world case study. Whether you’re a software developer branching into ML, a statistician aiming to upskill, or a professional exploring AI-driven innovation, you’ll discover how to build in-demand ML expertise on your own schedule.