Machine Learning Engineer II

As a Machine Learning Engineer II at Cohere Health, your main responsibilities include designing, developing, and deploying advanced machine learning algorithms for various use cases. You'll work on building scalable production ML systems and maintain reusable codebases for data preprocessing, model training, and deployment. Collaborating with product managers and clinical teams to align your models with the core objectives of the company is also crucial. Moreover, your expertise in model maintenance and optimization will play a key role in ensuring the success of our implementations.

To apply for the Machine Learning Engineer II position at Cohere Health, you should have a master's degree in computer science, machine learning, mathematics, or a similar field, along with at least 2 years of applied machine learning experience in the industry. It is essential to have a strong understanding of model building, maintenance, and optimization for production use. Additionally, you should possess expertise in Python and experience with deep learning frameworks like PyTorch, as well as practical experience in building deep learning models, particularly for NLP tasks.

In the Machine Learning Engineer II role at Cohere Health, proficiency in Python is crucial, as it is the primary programming language used for developing machine learning algorithms. Familiarity with deep learning frameworks such as PyTorch is highly desirable. Additionally, experience with AWS tools, particularly SageMaker Studio, is a bonus, as it streamlines the deployment and management of ML models. Being comfortable with handling unstructured healthcare data and utilizing techniques like OCR for document understanding will also enhance your contributions to the team.

The salary range for a Machine Learning Engineer II at Cohere Health is between $110,000 and $130,000 annually. This range reflects the company’s commitment to offering competitive compensation while factoring in skills, experience level, and internal alignment. In addition to salary, the total benefits package includes health insurance, a 401k plan, and bonus opportunities.

Cohere Health is recognized as one of the best places to work, having received multiple awards for workplace culture and innovation. For Machine Learning Engineers, the environment is collaborative and growth-oriented, emphasizing empathy and inclusivity. By joining the team, you become part of a mission-driven organization focused on improving healthcare delivery. The rich blend of advanced technology, clinical expertise, and a passion for making a positive impact sets Cohere Health apart, making it an exciting place for engineers to advance their careers.

When answering this question, highlight specific projects or models you've worked on that relate to healthcare. Discuss the algorithms you used, the outcomes, and how they impacted clinical practices. Make sure to connect your experience with the responsibilities of the Machine Learning Engineer II role at Cohere Health, emphasizing your ability to address real-world challenges in the healthcare domain.

To address this question, outline your process for building scalable systems, including techniques such as model optimization, load testing, and using cloud services like AWS for deployment. It’s essential to demonstrate your understanding of scalable architecture and past experiences where you've implemented such solutions successfully in your previous roles.

Effective evaluation is crucial in machine learning. You should explain the metrics you commonly use, such as accuracy, precision, recall, and F1-score, and how you interpret these metrics based on project goals. Share examples of how you iterated on models based on evaluation results, aligning them with the needs of stakeholders at Cohere Health.

Unstructured data is often challenging but important in healthcare. Describe your methods for processing unstructured data, such as natural language processing (NLP) techniques or feature extraction strategies. Provide examples of projects where you’ve successfully transformed unstructured data into actionable insights and how this might relate to the work at Cohere Health.

Collaboration with cross-functional teams is vital at Cohere Health. Share a specific example that showcases your ability to communicate technical concepts clearly to non-technical stakeholders, such as clinicians or product managers. Explain how this collaboration led to a successful outcome for a project or initiative involving machine learning.

In a rapidly evolving field like machine learning, staying informed is key. Discuss the resources you utilize, such as academic journals, online courses, webinars, and community involvement. Share how you've applied any recent advancements or insights into your work, particularly those that might benefit your role as a Machine Learning Engineer II at Cohere Health.

Use the STAR method (Situation, Task, Action, Result) to structure your answer. Focus on a specifically challenging ML-related issue you encountered, the measures you took to address it, and the positive outcome. Make sure to relate this experience to potential challenges you may face at Cohere Health, demonstrating your problem-solving abilities.

Effective prioritization is crucial, especially in a dynamic environment. Talk about your methods for assessing project urgency and importance, and how you communicate with your team and stakeholders to ensure alignment on priorities. Examples of successfully managing multiple projects will strengthen your answer, demonstrating your organizational skills.

Express your knowledge of generative AI concepts and technologies, particularly how they can transform healthcare scenarios. Share relevant examples of generative AI applications, focusing on their innovative potential in improving patient outcomes or administrative workflows, which directly aligns with Cohere Health’s mission.

Here, emphasize your alignment with Cohere Health's mission and core values. Discuss your passion for improving healthcare through technology and how your personal and professional values align with the company culture. This is the perfect opportunity to express your enthusiasm for contributing to a team that values empathy, diversity, and impactful innovation.