Full Stack Software Engineer - Healthcare

Princeton Biopartners
London
1 month ago
Applications closed

Related Jobs

View all jobs

Software Engineer

Co-Founder / CTO Opportunity – AI Tech Recruitment Start-Up

Co-Founder / CTO Opportunity – AI Tech Recruitment Start-Up

Senior Software Engineer, Machine Learning

Full Stack Developer

Machine Learning Engineer, Generative AI InnovationCenter

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.

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.

Jobs Careers

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.

Jobs

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.

Jobs

Machine Learning Jobs in the Public Sector: Opportunities Across GDS, NHS, MOD, and More

Machine learning (ML) has rapidly moved from academic research labs to the heart of industrial and governmental operations. Its ability to uncover patterns, predict outcomes, and automate complex tasks has revolutionised industries ranging from finance to retail. Now, the public sector—encompassing government departments, healthcare systems, and defence agencies—has become an increasingly fertile ground for machine learning jobs. Why? Because government bodies oversee vast datasets, manage critical services for millions of citizens, and must operate efficiently under tight resource constraints. From using ML algorithms to improve patient outcomes in the NHS, to enhancing cybersecurity within the Ministry of Defence (MOD), there’s a growing demand for skilled ML professionals in UK public sector roles. If you’re passionate about harnessing data-driven insights to solve large-scale problems and contribute to societal well-being, machine learning jobs in the public sector offer an unparalleled blend of challenge and impact. In this article, we’ll explore the key reasons behind the public sector’s investment in ML, highlight the leading organisations, outline common job roles, and provide practical guidance on securing a machine learning position that helps shape the future of government services.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.