Sr. Engineering Manager, Machine Learning at AKASA

South San Francisco, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years), Mid-level (3 to 4 years)Experience Level

Full TimeJob Type

UnknownVisa

AI & Machine Learning, Consumer SoftwareIndustries

Skills

Key technologies and capabilities for this role

Model fine-tuningInferenceEvaluationDeploymentLLM stackInfrastructureTooling

Questions & Answers

Common questions about this position

What is the work arrangement or location policy for this role?

The position is hybrid and based in South San Francisco, with Wednesday co-working days expected for local R&D teams.

What is the salary for this position?

This information is not specified in the job description.

What are the key responsibilities that show required skills for this role?

The role requires leading a team of Machine Learning Engineers and hands-on experience with the LLM stack, including model fine-tuning, inference, evaluation, deployment, and developing infrastructure for the model development lifecycle.

What is the company culture like at AKASA?

AKASA fosters a welcoming environment for diverse perspectives, is certified as a Great Place to Work for four years, and has been recognized as America’s Best Startup Employers by Forbes, Best Companies for Remote Workers by Quartz, and Best Places to Work by multiple outlets.

Who does this role report to, and what does that suggest for strong candidates?

The role reports to the VP of Engineering, who oversees Machine Learning Engineering, Product Engineering, Core Platform Engineering, and Data Platform and Analytics, indicating strong candidates should have leadership experience in ML engineering and the ability to collaborate across engineering teams.

AKASA

Automates revenue cycle management processes

About AKASA

AKASA offers technology solutions that enhance efficiency and revenue outcomes for healthcare organizations by using a mix of computer vision-based Robotic Process Automation (RPA), machine learning, and human-in-the-loop automation. Their services streamline complex Revenue Cycle Management (RCM) workflows, allowing healthcare staff to focus on more meaningful tasks. Unlike competitors, AKASA specifically targets operational inefficiencies in revenue cycle departments, helping clients like Methodist Health System achieve significant gross yield increases. The company's goal is to empower healthcare organizations to improve their operational efficiency and patient experience.

San Francisco, CaliforniaHeadquarters

2018Year Founded

$199.4MTotal Funding

SERIES_CCompany Stage

AI & Machine Learning, HealthcareIndustries

51-200Employees

Benefits

Flexible vacation policy.

Generous coverage for health, dental, and vision insurance.

Free membership to One Medical for you and your family.

Health FSA account.

Full employee coverage for life insurance.

401K plan.

Risks

Generative AI adoption may increase competition, eroding AKASA's market share.

Healthcare's cautious approach may slow adoption of AKASA's new technologies.

Integration with existing EHR systems may pose implementation challenges for AKASA.

Differentiation

AKASA uses AI to automate complex revenue cycle tasks in healthcare.

Their solutions decrease A/R days by 13% and increase efficiency by 86%.

AKASA's tailored AI models outperform generic models like GPT-4 by up to 40%.

Upsides

AKASA's GenAI solutions reduce prior authorization time by up to 50%.

Over 70% of healthcare organizations are exploring generative AI for revenue cycle management.

AKASA's Medical Coding enhances efficiency and accuracy in the $23B medical coding field.

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