At a Glance
- Tasks: Develop and validate machine learning models to improve cancer care.
- Company: Flatiron Health is a healthtech company transforming cancer care through data.
- Benefits: Enjoy a collaborative environment, flexible work options, and the chance to make a real impact.
- Why this job: Join a mission-driven team using AI to revolutionise oncology research and patient care.
- Qualifications: 3+ years in ML, experience with NLP and LLMs preferred; passion for solving real-world problems.
- Other info: Opportunity to work cross-functionally with diverse teams across the globe.
The predicted salary is between 30000 - 50000 £ per year.
We’re looking for a Machine Learning Engineer to help us accomplish our mission to improve and extend lives by learning from the experience of every person with cancer. Are you ready to be the next changemaker in cancer care?
Flatiron Health is a healthtech company using data for good to power smarter care for every person with cancer, around the world. Flatiron partners with cancer centers in the US, Europe and Asia to transform patients’ real-life experiences into real-world evidence and create a more modern, connected oncology ecosystem. Our multidisciplinary teams include oncologists, data scientists, software engineers, epidemiologists, product experts and more. Flatiron Health is an independent affiliate of the Roche Group.
What You'll Do
At Flatiron, we’re advancing the use of machine learning, generative AI, and natural language processing to extract clinically relevant information from unstructured medical notes for use in oncology research. The Data Curation team is helping to build these next generation research data products, developing and applying ML models to capture a complete picture of the patient journey. As part of our team, you will develop and validate models to solve applied clinical problems and help build towards our vision of the future of machine learning at Flatiron. Engaging with a cross-functional group of stakeholders across our teams in Europe, Japan, and the US you will contribute to model development projects from scoping through to productionization and delivery.
In addition, you'll also:
- Interface with internal scientific stakeholders and customers to understand what data they need to conduct high quality research.
- Build models to turn raw clinical data into high quality research variables, drawing on your knowledge of LLMs, traditional ML, and NLP techniques to determine the right methods to use for a given problem.
- Work with quantitative scientists and oncologists to validate that your models can be used to generate sound scientific insights.
- Collaborate with other Data Scientists to accelerate our ML capabilities and develop novel approaches to clinical data extraction from unstructured health records.
- Work cross-functionally with software engineers to productionize, scale, and monitor your models.
Who You Are
You're a product-focused data scientist, with experience in leveraging ML and NLP to solve real-world problems. You're excited by the prospect of rolling up your sleeves to tackle meaningful problems each and every day. You’re a kind, passionate and collaborative problem-solver who seeks and gives candid feedback, and values the chance to make an important impact.
You have 3+ years of relevant working experience in a technical capacity, with a focus on ML. Prior experience with NLP and LLMs is strongly preferred. You have a strong background in applying ML to solve real-world problems and a solid grasp of the underlying statistical fundamentals of ML. You are excited to work in a startup environment, think creatively and be scrappy to get the job done. You have a nose for value and empathy for your customers. You have collaborated with other technical team members in a production development environment using formal version control, Python, and SQL.
Optional:
You have ML experience in a healthcare setting. You have experience with the risks of bias in machine learning, health equity research/analysis or have worked with underrepresented groups in a clinical research setting.
If this sounds like you, you'll fit right in at Flatiron.
Machine Learning Engineer employer: Job Traffic
Contact Detail:
Job Traffic Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer
✨Tip Number 1
Familiarise yourself with Flatiron Health's mission and values. Understanding their focus on improving cancer care through data will help you align your answers during interviews and demonstrate your passion for the role.
✨Tip Number 2
Network with current or former employees of Flatiron Health on platforms like LinkedIn. Engaging in conversations about their experiences can provide valuable insights into the company culture and expectations, which you can leverage in your application.
✨Tip Number 3
Stay updated on the latest trends in machine learning, NLP, and healthcare technology. Being knowledgeable about recent advancements will not only boost your confidence but also allow you to discuss relevant topics during interviews.
✨Tip Number 4
Prepare to discuss specific projects where you've applied ML and NLP techniques. Be ready to explain your thought process, challenges faced, and how you overcame them, as this will showcase your problem-solving skills and technical expertise.
We think you need these skills to ace Machine Learning Engineer
Some tips for your application 🫡
Understand the Role: Before applying, make sure you fully understand the responsibilities and requirements of the Machine Learning Engineer position at Flatiron Health. Familiarise yourself with their mission and how your skills can contribute to improving cancer care.
Tailor Your CV: Customise your CV to highlight relevant experience in machine learning, natural language processing, and any healthcare-related projects. Use specific examples that demonstrate your problem-solving skills and technical expertise.
Craft a Compelling Cover Letter: Write a cover letter that reflects your passion for the role and the company’s mission. Discuss your experience with ML and NLP, and explain how you can help Flatiron Health achieve its goals. Be sure to convey your collaborative spirit and eagerness to tackle meaningful challenges.
Showcase Relevant Projects: If you have worked on projects related to machine learning or healthcare, include them in your application. Describe your role, the technologies used, and the impact of your work. This will help demonstrate your practical experience and ability to apply your skills effectively.
How to prepare for a job interview at Job Traffic
✨Understand the Company’s Mission
Before your interview, make sure you understand Flatiron Health's mission to improve cancer care. Familiarise yourself with their work in using data for good and how machine learning plays a role in this. This will show your genuine interest in the company and its goals.
✨Showcase Your Technical Skills
Be prepared to discuss your experience with machine learning, natural language processing, and large language models. Bring examples of past projects where you've applied these skills to solve real-world problems, especially in healthcare if applicable.
✨Prepare for Collaborative Scenarios
Since the role involves working with cross-functional teams, think of examples that demonstrate your ability to collaborate effectively. Be ready to discuss how you’ve worked with data scientists, software engineers, or oncologists in previous roles.
✨Ask Insightful Questions
Prepare thoughtful questions about the team dynamics, ongoing projects, and the challenges they face in machine learning applications. This not only shows your enthusiasm but also helps you gauge if the company culture aligns with your values.