Who we are:
Apella is applying computer vision and machine learning to improve the standard of care in the most critical aspect of healthcare: surgery. We build applications to enable surgeons, nurses, and hospital administrators to deliver the highest quality care.
What you are:
We’re looking for a machine learning engineer who thrives on leveraging their AI and computer vision proficiency to solve impactful problems, particularly in getting the right data into the right place to build effective ML models. You are a collaborative team player who flourishes in a startup environment working up and down the technical stack with software engineers on product and infrastructure, taking broad ideas and specifications and doing whatever it takes to launch them into exceptional product experiences. As an impactful member of our team, you’ll also have the unique opportunity to help shape the culture of Apella’s machine learning function and abundant opportunities for career growth.
In this role you'll:
- Collaborate closely with engineering, product, and data science teams to understand business challenges and the potential for machine learning and AI solutions.
- Develop tools and automate manual processes to improve operational efficiency, accelerate experimentation velocity, and minimize human error.
- Build, integrate, and monitor the end-to-end lifecycles of large-scale, distributed machine learning systems.
- Investigate model performance and identify data quality and performance issues.
What you'll bring:
- Experience with designing and building tooling around annotation / curation / management of ML datasets.
- Proficiency in handling real-world, high volume and velocity datasets, particularly familiarity with image and video formats.
- Proficiency in using AI tools and techniques to expedite product development.
- Passion for writing readable, tested, and efficient code in collaboration with other engineers.
- 5+ years of experience working with machine learning systems, covering the full production workflow and monitoring.
- A strong commitment to craftsmanship and producing high-quality work.
- Familiarity with developing SaaS products for business customers.
Good to have:
- Experience working in healthcare or other regulated industries.
- Hands on experience with video ML inference
- Experience with DAG frameworks