Lead of Machine Learning Engineering, RNA Therapeutics

GlaxoSmithKline
London
1 week ago
Applications closed

Related Jobs

View all jobs

Lead of Machine Learning Engineering, RNA Therapeutics

Lead AI/ML Engineer

Data Science Manager

Lead Machine Learning Engineer

ML (Machine Learning) Engineer

Data Scientist

Site Name:

London The Stanley Building

For a complete understanding of this opportunity, and what will be required to be a successful applicant, read on.Posted Date:

Sep 5 2024At GSK we see a world in which advanced applications of machine learning and AI will allow us to develop novel therapies to existing diseases and to quickly respond to emerging or changing diseases with personalized treatments, driving better outcomes at reduced cost with fewer side effects. It is an ambitious vision that will require the development of products and solutions at the cutting edge of machine learning and AI. If that excites you, we'd love to chat.The AI/ML RNA Therapeutics team applies machine learning and AI methods to fundamental problems in RNA biology and biochemistry domain in order to accelerate the discovery and development of novel RNA therapeutics. Improved target identification and therapeutic design in this space has the potential to be transformative, empowering scientists to make better and faster data-driven decisions about potential therapeutics.We are looking for a

Lead of ML Engineering – RNA Therapeutics . This is a technical management track role with responsibility for direct reports. The candidate should be comfortable being accountable for setting the direction, standards and culture of a machine learning engineering sub-team, with demonstrable expertise across machine learning, software engineering and biology. Equally important will be excellent communication, interpersonal and organisational skills, and the ability to represent and transmit the values and principles of our organisation.The AI/ML team is built on the principles of ownership, accountability, continuous development, and collaboration. We hire for the long term, and we're motivated to make this a great place to work. Our leaders will be committed to your career and development from day one.In this role you will:Lead a machine learning engineering team specialising in fundamental problems in RNA biology and chemistryManage complex, multi-quarter, cross-functional projectsBe a standard bearer for data science and software engineering best practices within the organisationDevelop plans to meet requirements, organize a team capable of executing the plans, and lead and track delivery.Maintain a safe and inclusive team environment in which people thriveOperate in a transparent way, communicating clearly and accurately to leadership and the broader organizationDevelop a high-performing team through coaching, feedback and ensuring opportunities for growthQualifications & Skills:We are looking for professionals with these required skills to achieve our goals:Graduate studies in Computer Science or Applied Math, undergraduate studies in Computer Science and relevant graduate studies in the life sciences with a focus on AI/ML techniques, or undergraduate studies in Computer Science and equivalent work history. Candidates with graduate studies in CS and biological sciences or equivalent work history will be highly competitiveTrack record as an independent contributor capable of end-to-end development of ML-powered products for biological or pharmaceutical applicationsAdvanced Python programming skills and a track record of delivering robust software solutions3+ years experience in a technical lead or engineering manager role with direct reports5+ years experience of professional software development practices: code standards, code review, version control, CI/CD, testing, documentation, Agile, with the ability to mentor others in these practicesProficiency with standard deep learning algorithms and model architectures, including sequence or graph based methodsIn depth knowledge in machine learning best practices, scalable training and deploymentPreferred Qualifications & Skills:If you have the following characteristics, it would be a plus:PhD in Machine Learning or Computer ScienceExperience working with large ML-powered systems in a production settingKnowledge in molecular biology, disease biology and/or biochemistryPeer reviewed publications in major AI conferencesClosing Date for Applications:

Thursday 29th August 2024 (COB)Please take a copy of the Job Description, as this will not be available post closure of the advert.When applying for this role, please use the ‘cover letter’ of the online application or your CV to describe how you meet the competencies for this role, as outlined in the job requirements above.Why GSK?GSK is a global biopharma company with a special purpose – to unite science, technology and talent to get ahead of disease together – so we can positively impact the health of billions of people and deliver stronger, more sustainable shareholder returns – as an organisation where people can thrive. We prevent and treat disease with vaccines, specialty and general medicines. We focus on the science of the immune system and the use of new platform and data technologies, investing in four core therapeutic areas (infectious diseases, HIV, respiratory/ immunology and oncology).Our success absolutely depends on our people. While getting ahead of disease together is about our ambition for patients and shareholders, it’s also about making GSK a place where people can thrive. We want GSK to be a place where people feel inspired, encouraged and challenged to be the best they can be. A place where they can be themselves – feeling welcome, valued, and included. Where they can keep growing and look after their wellbeing. So, if you share our ambition, join us at this exciting moment in our journey to get Ahead Together.As an Equal Opportunity Employer, we are open to all talent.We believe in an agile working culture for all our roles. If flexibility is important to you, we encourage you to explore with our hiring team what the opportunities are.

#J-18808-Ljbffr

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 Leadership for Managers: Strategies to Motivate, Mentor, and Set Realistic Goals in Data-Driven Teams

Machine learning (ML) has become an indispensable force in the modern business world, influencing everything from targeted marketing campaigns to advanced medical diagnostics. As industries integrate predictive algorithms and data-driven decision-making into their core operations, the need for effective leadership in machine learning environments has never been greater. Whether you’re overseeing a small team of data scientists or spearheading an enterprise-scale ML project, your leadership style must accommodate rapid innovation, complex problem-solving, and diverse stakeholder expectations. This guide provides actionable insights into how you can motivate, mentor, and establish achievable goals for your machine learning teams—ensuring they thrive in data-driven environments.

Top 10 Books to Advance Your Machine Learning Career in the UK

Machine learning (ML) remains one of the fastest-growing fields within technology, reshaping industries across the UK from finance and healthcare to e-commerce, telecommunications, and beyond. With increasing demand for ML specialists, job seekers who continually update their knowledge and skills hold a significant advantage. In this article, we've curated ten essential books every machine learning professional or aspiring ML engineer in the UK should read. Covering foundational theory, practical implementations, advanced techniques, and industry trends, these resources will equip you to excel in your machine learning career.

Navigating Machine Learning Career Fairs Like a Pro: Preparing Your Pitch, Questions to Ask, and Follow-Up Strategies to Stand Out

Machine learning (ML) has swiftly become one of the most in-demand skill areas across industries, with companies leveraging predictive models and data-driven insights to solve challenges in healthcare, finance, retail, manufacturing, and beyond. Whether you’re an early-career data scientist aiming to break into ML, a seasoned engineer branching into deep learning, or a product manager exploring AI-driven solutions, machine learning career fairs offer a powerful route to connect with prospective employers face-to-face. Attending these events can help you: Network with hiring managers and technical leads who make direct recruitment decisions. Gain insider insights on the latest ML trends and tools. Learn about emerging job roles and new industry verticals adopting machine learning. Showcase your interpersonal and communication skills, both of which are increasingly important in collaborative AI/ML environments. However, with many applicants vying for attention in a bustling hall, standing out isn’t always easy. In this detailed guide, we’ll walk you through how to prepare meticulously, pitch yourself confidently, ask relevant questions, and follow up effectively to land the machine learning opportunity that aligns with your ambitions.