Machine Learning Engineer Ii

1 month ago

Auckland City, New Zealand Clover Health Full time

Clover is reinventing healthcare by working to keep people healthier._

We value diversity — in backgrounds and in experiences. Healthcare is a universal concern, and we need people from all backgrounds and swaths of life to help build the future of healthcare. Clover's engineering team is empathetic, caring, and supportive. We are deliberate and self-reflective about the team and culture that we are building, looking for engineers that are not only strong in their own aptitudes but care deeply about aiding in each other's growth.

We're looking for a Machine Learning Engineer II to help us build a revolutionary new health care business. Counterpart Health uses Machine Learning (including NLP/LLMs) to leverage our data to help keep patients healthy and out of the hospital by getting them targeted care. By predicting avoidable adverse events, our ML infrastructure is central to working on our central mission, and has a direct impact on improving clinical care. You will help build systems and tools that support the data needs of a diverse organization and contribute to the expansion of the ML capabilities of our Platform.

**As a Machine Learning Engineer II, you will**:

- Create, debug, interpret and improve production ML models.
- Design, implement and validate pieces of our high-reliability, distributed platforms for ML.
- Build the tools and validation processes that help Counterpart translate insights into action at scale.
- Use existing commercial and open source tools to create a robust production platform.
- Work closely with Counterpart's Data Science and Engineering teams to ensure that the ML platform is providing real value.
- Document, iterate, and provide tutorials to ensure Data Scientists and Engineers are able to use your tools easily.

**Success in this role looks like**:

- Within 90 days: Successfully able to deliver a well-scoped project that improves machine learning models or systems.
- Within 6 months: Able to increasingly own larger pieces of the system and work more autonomously in places you have experience.
- In the future: Growing in ownership to increasingly large and complex pieces of our ML models and systems.

**You will love this job if**:

- You want to create **impact **with your work by finding ML-driven insights in the data to unlock value and improve health outcomes for real people.
- You are comfortable acting **autonomously** on tasks in ambiguous and changing environments.
- You value **collaboration** and feedback. You can communicate technically in clear terms— to your teammates and across the technology team more broadly. You are willing and able to help your teammates grow by providing (and receiving) respectful and constructive feedback, and disclosing your unique insights with everyone.
- You enjoy working in a **fluid environment**, defined by priorities that adapt to our larger goals. You can bring clarity to ambiguity on projects while remaining open-minded to new information that might change your mind.
- You are not hesitant to jump in to help fix things that are broken and you are encouraged to make **sustainable systems**. You are happy to fill in the gaps to reach a goal where necessary, even if it does not always fit your job description.
- You have a genuine interest in what good technology can do to help people and have a **positive attitude** about tackling hard problems in an important industry.

**You should get in touch if**:

- You have 3+ years of experience in Machine Learning Engineering or related roles in technology enabled companies, healthcare experience preferred but not required.
- You have experience with Python, Python data science libraries (numpy, pandas, sklearn, tensorflow, pytorch, etc.), and deploying Python apps into production environments.
- You have a solid foundation in feature engineering, feature selection, and AI techniques.
- You have experience interpreting, modifying, and debugging the inputs and outputs of production ML models.
- You have both built and refactored parts of distributed systems, especially ML systems.

**Benefits Overview**:

- Financial Well-Being: Our commitment to attracting and retaining top talent begins with a competitive base salary and equity opportunities. Additionally, we offer a performance-based bonus program and regular compensation reviews to recognize and reward exceptional contributions.
- Physical Well-Being: We prioritize the health and well-being of our employees and their families by offering comprehensive group medical coverage that include coverage for hospitalization, outpatient care, optical services, and dental benefits.
- Mental Well-Being: We understand the importance of mental health in fostering productivity and maintaining work-life balance. To support this, we offer initiatives such as No-Meeting Fridays, company holidays, access to mental health resources, and a generous annual leave policy. Additionally, we embrace a remote-first culture that supports collaboration

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