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- Tasks: Lead a talented team to innovate drug discovery through machine learning.
- Company: Join a cutting-edge biotech company focused on groundbreaking innovations.
- Benefits: Collaborate with experts, enjoy career growth, and work in a dynamic environment.
- Why this job: Be part of a mission-driven team making a real impact in healthcare.
- Qualifications: Strong software engineering skills and experience in machine learning and biotech.
- Other info: Apply quickly; this popular position may close early!
The predicted salary is between 54000 - 84000 £ per year.
An impressive opportunity to work as a Senior Machine Learning Engineer has arisen for an exciting start-up company and their incredible team.
This role is a marvellous opportunity to help develop machine learning models and algorithms to assist in the data analysis of medical imaging. The company are in the process of producing ground-breaking work towards their fundamental goal of diagnosing and treating cancer at its most actionable and early stages.
This role will provide the opportunity to work to work alongside experienced healthcare professionals and with clinical healthcare data. As well as, working hard with other software and training computers to recognise and understand medical imaging data and subsequently make streamlined decisions based on the data from said images.
If you have strong experience in machine learning, specifically in medical image analysis the please read below.
Responsibilities:
- Work across different aspects of machine learning research, assisting in developing ML models and analysing medical imaging data
- Combine divergent tooling around medical images to form united pipelines and software solutions
- Produce algorithms for medical image analysis to detect patterns and trends in cancer growth
- Improving the accuracy of already deployed ML models by implementing superior MLOps
- Facilitate data driven science discoveries in biology and healthcare
- Build for significant growth and having the ability to scale challenges – achieving a high degree of robustness and performance
Background:
- M.Sc in computer science or engineering
- A developed understanding of machine learning and computer vision, including MLOps
- Acute coding skills in Python and other programming languages
- Knowledge of object-oriented-programming and software architectures in C++ / Java / C#
- Experience in cloud-based computing settings
- Strong understanding and excellent skills in Linux, shell scripting, containerization etc.
- An ability to write clear code along with capability to assess and devise software requirements
- Fluent professional level English along with personable communication skills
- Technical curiosity and adventure around applying machine learning in healthcare, looking to push the boundaries of science!
Desired experience:
- Ph.D. in relevant area
- Understanding of PyTorch, Tensorflow and platforms like TFX, Neptune.ai, MLflow, Weights & biases etc.
- Previous experience working in computer vision or machine learning
- Knowledge of digital pathology
- Awareness and prior experience in Life Science and/or computational biology
Following your application Mark Njiriri, a specialist AI recruiter will discuss the opportunity with you in detail.
He will be more than happy to answer any questions relating to the industry and the potential for your career growth. The conversation can also progress further to discussing other opportunities, which are also available right now or will be imminently becoming available.
This position has been highly popular, and it is likely that it will close prematurely. We recommend applying as soon as possible to avoid disappointment.
Senior Machine Learning Engineer employer: Barrington James
Contact Detail:
Barrington James Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer
✨Tip Number 1
Make sure to showcase your experience in leading and mentoring engineering teams. Highlight specific examples where you've successfully guided a team through complex projects, especially in the biotech or pharmaceutical sectors.
✨Tip Number 2
Demonstrate your technical leadership skills by discussing your experience with architectural design and tooling choices. Be prepared to share how your decisions have positively impacted project outcomes in previous roles.
✨Tip Number 3
Familiarize yourself with the latest advancements in machine learning accelerator hardware. Being able to discuss these technologies and their applications in drug discovery will set you apart from other candidates.
✨Tip Number 4
Network with professionals in the biotech industry. Engaging with others in the field can provide insights into current trends and challenges, which you can reference during discussions with Amelia Pudney.
We think you need these skills to ace Senior Machine Learning Engineer
Some tips for your application 🫡
Understand the Role: Take the time to thoroughly read the job description. Understand the key responsibilities and required skills for the Senior Machine Learning Engineer position, as this will help you tailor your application.
Highlight Relevant Experience: In your CV and cover letter, emphasize your experience in software engineering, platform engineering, and machine learning development. Be specific about your contributions to drug discovery projects and any leadership roles you've held.
Showcase Technical Leadership: Demonstrate your ability to lead and mentor teams in your application. Provide examples of how you've made technical decisions and influenced architectural design in previous roles.
Express Your Passion: Convey your enthusiasm for the biotech industry and your commitment to driving innovation in drug discovery. A personal touch can make your application stand out, so share why this role excites you.
How to prepare for a job interview at Barrington James
✨Showcase Your Technical Leadership
Be prepared to discuss your experience in leading and mentoring engineering teams. Highlight specific examples where you inspired your team or made critical technical decisions that positively impacted a project.
✨Demonstrate Cross-Functional Collaboration
Since this role involves working closely with machine learning researchers, be ready to share experiences where you successfully collaborated with different teams. Emphasize your ability to communicate complex technical concepts to non-technical stakeholders.
✨Discuss Your Experience in Drug Discovery
Given the focus on biotech and pharmaceutical projects, make sure to articulate your relevant industry experience. Talk about specific drug discovery projects you've worked on and how your contributions led to innovative outcomes.
✨Prepare for Technical Questions
Expect to face technical questions related to machine learning algorithms, software architecture, and platform engineering. Brush up on your knowledge of the latest tools and technologies in the field, and be ready to explain your thought process in solving complex problems.
