Who we are:
K Health is a venture-backed, fast-growing start-up with a mission to use the power of shared knowledge to get everyone access to higher quality, more affordable health care. We're looking for mission-driven individuals to join our growing team and help us eliminate healthcare inequalities and build a better, healthier future for us all.
Named as one of FastCompany's Most Innovative Health Companies of 2022 and to the 2021 CNBC Disruptor 50 list, K Health is using Artificial Intelligence (AI) to build the smartest digital healthcare platform in existence. Our data-driven app brings together the knowledge of thousands of doctors and the anonymous medical records of millions of people to help diagnose and treat what's wrong. We offer a free symptom checker and 24/7 access to doctors to ask questions, refill prescriptions, get care for your kids, and more. Right from your phone—no insurance needed.
Since we were founded in 2016, K Health has raised over $270M in VC funding and our Series E funding round brought us to Unicorn status. Our current partners include the Mayo Clinic Platform, Anthem, and Maccabi Health Services.
About the role:
We are seeking a highly motivated and experienced Machine Learning Engineer to join our team. As a Machine Learning Engineer, you will be responsible for designing and implementing machine learning systems and models that will be used to solve complex business problems. You will work closely with data scientists and software developers to develop and deploy these models into production. If you are passionate about machine learning and want to work on cutting-edge projects with a talented and dynamic team, we encourage you to apply.
What you'll be doing:
- Design and implement machine learning systems, tools and models.
- Studying, transforming, and converting data science prototypes.
- Optimize and fine-tune machine learning models for performance, accuracy, and scalability.
- Collaborate with software developers to integrate machine learning models into production systems.
- Monitor and evaluate the performance of deployed models and continually improve them through ongoing testing, experimentation, and refinement.
- Stay up-to-date with the latest advancements in machine learning and apply them to improve the company's products and services.
What we're looking for:
- 2+ years of experience designing and implementing machine learning tools and systems.
- 3+ years of industry experience with Python in a programming intensive role.
- Experience with workflow management frameworks such as Kubeflow pipelines, AirFlow or sagemaker pipelines.
- Good understanding of software development principles and practices.
- Strong problem-solving skills and ability to work independently and as part of a team.
- Experience with cloud-based machine learning platforms such as AWS, Azure, or Google Cloud.
- Experience with deploying machine learning models in production environments.
- Familiarity with DevOps practices and tools.
Benefits & Perks: #LI-Hybrid
- 20 paid vacation days, 18 days sick leave, and 10 3-day weekends
- Hybrid work schedule with team meals and stocked fridges
- Commuter Benefits
- Community focused events
- Pension Plan
- Stipend per day for food
- Stock options for every full-time employee
- Vocational Studies Fund
K Health offers competitive compensation packages along with stock options based on industry benchmarks for function, level, and geographic location. Offer amounts are determined by multiple factors such as a candidate's experience and expertise.
We're deeply committed to building teams as diverse as the patients we serve and strive to cultivate an environment where everyone can bring their most authentic self to work. We depend on our differences to make our team stronger, our workplace more dynamic, and our product accessible to all of our users.
K Health is proud to be an Equal Opportunity Employer and considers applicants for employment regardless of race, ethnicity, religion, color, national origin, ancestry, disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, sexual orientation, pregnancy, childbirth and breastfeeding, age, citizenship, military or veteran status, or any other class protected by applicable federal, state, and local laws.
