Biochemical Engineer

ADLIB Recruitment | B Corp
Oxfordshire
1 month ago
Applications closed

Biochemical Engineer


  • Join an agile, forward-thinking company making a huge impact in the cultivated meat space.
  • A varied and unique role with hands-on bioprocessing responsibilities.
  • Play a pivotal role on the future direction of the company,


This is an opportunity to join a small but growing start-up working on a mission to support the cultivated meat space. With a unique focus on tissue structure and a novel bioreactor platform the team is looking for additional skills in the bioprocessing, biochemistry and biomanufacturing space to help bring this project to the next stage. This Biochemical Engineer will be a key team member contributing to technical project implementation and bioprocess design. We are looking for someone who thrives in a varied, fast-paced environment bringing expertise in small-scale bioreactor platform use.


What you’ll be doing:

  • Designing, developing, and optimising end-to-end pilot-scale bioreactor processes while also implementing enabling technologies to support scale-up.
  • Selecting, developing, and implementing experimental protocols and standard operating procedures (SOPs), as well as assisting in drafting risk assessments and maintaining health and safety standards.
  • Designing, planning, and executing R&D studies in alignment with project deliverables and timelines, analysing and summarising experimental results, and sharing key insights with the team.
  • Staying updated on the latest technologies and scientific literature is necessary to identify opportunities for process improvements.
  • There is also a need to take shared responsibility for out-of-hours bioprocess operations.


What experience you will need to apply:

  • An academic background in engineering with a Ph.D. in biochemical engineering, bioprocessing, biomanufacturing, or a related discipline. Or a Master’s degree in Chemical, Mechanical or Biomedical engineering + relevant experience within the bioprocessing space.
  • Demonstrable experience with small-scale bioreactor platforms.
  • Proven background in cell culture and familiarity with 3D culture systems.
  • Experience with computer-aided design (CAD) and data analysis using non-Excel tools such as Python, R, or MATLAB.
  • Proficiency in process flow diagrams (PFDs), piping and instrumentation diagrams (P&IDs), and HAZOP analysis.
  • The candidate should also be forward-thinking, proactive, passionate and curious.

Nice to have:

  • Experience with perfusion bioreactor systems, along with expertise in membrane characterisation.
  • Background in muscle or fat biology, cell metabolism, and development, as well as knowledge of the cultivated meat industry.


What you’ll get in return for your experience:

The opportunity to develop your scientific and engineering skills joining a passionate and modern company.

Oxfordshire based, full time on site.

Stock Options for being part of the early team.

Salary: dependent on applicant.


What's next?

If you are interested apply directly to this advert or if you have questions speak with Jazz Jones:

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.

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.

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.

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.