Sr. Machine Learning Engineer
AKASA · Remote · Remote - United States ·
COMPENSATION
€•• – ••k
Listed on the employer's job board (Ashby)
- Senior level role
- Hybrid (South SF)
- LLMs + Computer Vision
- Python + C++
- Healthcare AI
You will join a team of researchers and engineers to deploy machine learning models that streamline healthcare operations. Your work will directly impact customers by solving complex problems in medical document processing and claim prediction using large-scale clinical datasets.
The role requires owning the full lifecycle of ML services, from data pipeline development to model experimentation and deployment. You will collaborate with healthcare experts to create tools that amplify the capabilities of medical professionals.
What you'll do
- Own ML services end-to-end from problem discovery to deployment
- Develop pipelines for collecting and preprocessing high-quality data
- Write production-ready software with efficient, well-tested algorithms
- Build ML algorithms for LLMs, probabilistic inference, and computer vision
- Solve challenges like entity extraction and claim outcome prediction
- Create novel application-specific models built with ML at their core
What you'll need
- Master's degree in Computer Science or a similar field
- 5+ years of experience in machine learning and data engineering
- Proven track record of launching production ML systems from scratch
- Experience with LLMs, including open source deployment and agentic workflows
- Proficiency in Python, C++, or similar programming languages
- Development experience with cloud platforms like AWS, Spark, and k8s
- Knowledge of ML frameworks such as Pytorch, TensorFlow, and Scikit-Learn
Stack
- Python
- C++
- AWS
- Spark
- k8s
- Scikit-Learn
- Pytorch
- TensorFlow
How you'll work
- Hybrid role based in South San Francisco
- Mandatory office attendance every Wednesday for co-working
- Collaborate with R&D teams and healthcare experts
What you get
- Flexible paid time off
- Health, dental, and vision coverage
- Employer HSA contributions
- Generous parental leave policy
- Full life insurance coverage
- Home office stipend and internet reimbursement
- 401(K) plan