Accompany Health - Senior Machine Learning Engineer
Requirements
• 5+ years of software engineering experience, with a focus on building production-grade machine learning systems, backend infrastructure, or MLOps • Graduate degree in Computer Science, Statistics, or related quantitative field • Strong proficiency in Python and SQL, with the ability to create efficient and maintainable code for machine learning applications • Developing and maintaining ML pipelines for model training, evaluation, deployment (experience with tools like AWS Sagemaker or Bedrock is preferred) • Healthcare experience is valuable but not required • Developing and implementing modern LLM models and transformers and deploying ML models in a production environment • Designing and implementing best practices for model versioning, experimentation, and reproducibility • Continuously improving our ML infrastructure for stability, scalability, observability, and security • Developing internal tooling and libraries to enhance ML workflow efficiency • $175,000 - $200,000 a year • The base salary range for this full-time position is $175,000-$200,000 + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Our talent team can share more about the specific salary range for your preferred location during the hiring process. • For Patient Facing Roles • To keep our patients, communities and each other safe, you'll be required to comply with Accompany Health’s medical clearance requirements, including completing a TB screen and providing proof of immunity or vaccination for certain conditions. This is a condition of employment, and we make exceptions as required by law. Accommodation for religious and medical beliefs will be provided on a case by case basis.
Responsibilities
• Technical Leadership • Drive AI initiatives and collaborate with teams to leverage data effectively through model development and evaluation • Design and implement scalable Machine Learning infrastructure and solutions, ensuring reliability and performance • Help establish data engineering best practices and promote standards that enhance data accessibility across teams • Data Strategy & Architecture • Create and maintain optimal AI pipeline architecture with high observability and robust operational characteristics • Champion responsible AI development by implementing and reviewing models that maximize data value while ensuring fairness and equity • Assemble large, complex data sets that address functional and strategic requirements • Collaboration & Enablement • Partner with other teams such as; Executive, Product, Clinical, Data, and Design • Identify, design, and implement process improvements to enhance efficiency and scalability • Create tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader • Quality & Innovation • Develop efficient, reliable AI pipelines with strong monitoring and observability • Navigate and optimize our data ecosystem to drive meaningful insights • Design and implement comprehensive evaluation frameworks and benchmarks to rigorously assess model performance, accuracy and reliability • What makes you a fit for the team: • Your entrepreneurial mindset and ability to articulate complex technical ideas will be essential as you collaborate across our remote team to solve novel problems at the intersection of AI and compassionate care delivery
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