Senior Machine Learning Engineer

Data Science               ·                Remote                 ·                 Full time

Senior Machine Learning Engineer

Location: Remote

Type: Full time

Department: Data Science

About HealthRhythms 

Backed by elite Silicon Valley VCs and strategics ($40M), our mission is to alleviate unnecessary suffering by bringing mental health into the modern era of medicine. The market now recognizes that there is no health without mental health.  By combining the multi-dimensional sensing capabilities of mobile phones with the power of embedded and cloud computing platforms and novel AI algorithms, we continuously, objectively, and accurately measure mental health status for the very first time. We are realizing the vision of precision medicine for mental health by anticipating clinical deterioration before it reaches crisis proportions and by delivering personalized, just-in-time interventions based on each patient’s own behavioral profile.  

Our deep tech solution founded on 35 years of empirical evidence – led by our four co-founders and over 957 peer reviewed papers between them – addresses at the root cause the dual crises of insufficient access to mental health care and lack of measurement to assess intervention effectiveness. We have the advantage of a 35 year head start, best in class team, robust IP portfolio, and the largest mental health AI data set. 

UCHealth ($6B) declared “HealthRhythms will change the face of care,” and its #1 strategic priority is to deploy our platform to its 2.5M patients. UC invested twice and put its Chief Innovation Officer on our Board. Otsuka ($18B pharma) invested in HealthRhythms after assessing 500+ mental health companies, recognizing our potential to revolutionize the industry. Otsuka put its CMO on our Board. 

If joining an accelerating 100% remote startup, working with an extraordinary team who have united behind a mission to significantly improve the lives of patients  sounds meaningful and exciting to you, please read on and apply. 

As a senior machine learning engineer, you will:

• Lead the transformation of data science into a standardized and rigorous discipline, bridging the gap between traditional data science and production systems.
• Champion the development of tools, processes, and pipelines to streamline experimentation, modeling, and analysis, ensuring they are accessible and efficient for the data science team.
• Leverage your proficiency in Python and machine learning frameworks (XGBoost, CatBoost, scikit-learn, TensorFlow, PyTorch, Keras, etc) to architect and productionize machine learning models, including inference, monitoring, and alerting.
• Demonstrate exceptional leadership and communication skills, guiding and managing a team to achieve high-quality results.
• Create user-friendly libraries and resources to facilitate the ease of use for data scientists within the organization.

You have the following required experience:

• Advanced proficiency in Python and other relevant programming languages commonly used in machine learning.
• Proven experience in productionizing machine learning models with tangible accomplishments in this domain.
• Expertise in a machine learning framework such as XGBoost, CatBoost, scikit-learn, TensorFlow, PyTorch, Keras, etc, demonstrating a deep understanding of their intricacies.
• Demonstrated leadership experience in a similar role or capacity, with a track record of successful team management.
• A history of developing accessible and user-friendly libraries or tools for data science and machine learning practitioners.
• Previous responsibilities involve bridging the gap between data science and production systems, showcasing your commitment to closing this critical divide.

You’re a person who:

• Embodies a passion for standardization and rigor in data science, with a relentless drive to elevate the field within the organization.
• Thrives in a leadership role, taking ownership of projects and making data-driven decisions.
• Communicates effectively with team members, fostering collaboration and knowledge sharing.
• Exhibits a proactive and adaptable work style, staying abreast of evolving machine learning technologies and methods to maintain the organization’s competitive edge.
• Obsessed with making data science work easy while maintaining good engineering practices

Until now, mental health has been the only field of medicine lacking objective measurement. Health Rhythms captures data to create objective and actionable insights to improve mental health outcomes globally. Providers use Health Rhythms data to improve outcomes for their patients, and life science companies use Health Rhythms data to study and create better therapeutic solutions.

We believe that the 3B supercomputers in pockets around the world can be a platform to deliver mental health as a human right. If you believe the same, let’s talk. 

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