Sr. Engineering Manager, Machine Learning at Akasa

About AKASA At AKASA, our mission is to build the future of healthcare with AI. As the leading provider of generative AI solutions for the healthcare revenue cycle, we help health systems comprehensively capture and communicate the full patient clinical journey. By empowering health systems to streamline their operations, they can focus on what matters most - delivering quality patient care. We have raised over $205M in funding from investors such as Andreessen Horowitz, BOND, and Costanoa Ventures. This is the most exciting time to join AKASA. Revenue bookings for our new AI-native product suite have grown over 20x since launching in 2024. In this time, we have broken our record for the largest deal in company history three times consecutively. This growth is driven by the massive improvement we are generating for our customers across clinical quality and documentation accuracy, both top priority areas for health system leaders. Our deployments have been recognized nationally as "one of the most comprehensive real-world uses of GenAI in healthcare finance to date" (link [Upgrade to PRO to see link] Our customer base represents more than $120B+ in net patient revenue and includes the most innovative health systems in the country, like Cleveland Clinic, Duke, Stanford, and Johns Hopkins. Some of our recent recognitions include being named one of America's Top Startup Employers 2026 by Forbes, #1 most promising healthcare RCM startup of 2025 by Black Book Market Research, and one of the fastest-growing GenAI startups to watch by AIM Research. Our CEO was ranked among the “Top 50 Healthcare Technology CEOs” by the Healthcare Technology Report, and we have been certified as a “Great Place to Work” for the past 6 years in a row. We’re building on this momentum to redefine what’s possible in healthcare. We’re looking for exceptional people to help us accelerate that reality. About the Role This is an exciting opportunity to manage our Machine Learning Engineering (MLE) team. AKASA is a Machine Learning company from our inception. The combination of proprietary datasets, a talented research team, and customers that are eager to use LLMs sets up the MLE team for success. At its core, the MLE team has the exciting mandate of taking ML research improvements to production and ensuring that they create value for our customers. The ideal candidate for this role will be excited to collaborate across the stack, all the way from the research team to talking with users of our products. You will report to the VP of Engineering who oversees Machine Learning Engineering, Product Engineering, Core Platform Engineering, and Data Platform and Analytics. The AKASA office is located in South San Francisco. While we support remote work on a variety of teams, we have a strong Bay Area presence across the company. The local R&D teams come into the office every Wednesday for co-working days, which this role will be expected to attend. What You'll Do - Lead a talented team of engineers focused on improving AKASA’s machine learning capabilities and delivering cutting-edge products - Supervise and directly contribute across all parts of the LLM stack, including model fine-tuning, inference, evaluation, and deployment - Develop infrastructure and tooling to improve the model development lifecycle - Oversee a high-performing team via hands-on contributions and coaching - Translate business requirements into technical designs that work within constraints such as latency, cost, performance, and uptime - Set the vision and direction for the team and attract top talent to join AKASA Skills & Qualifications - MS or PhD in Computer Science preferred, with an emphasis in Machine Learning  - 7+ years of work experience in Machine Learning  - 5+ years of people management experience, including building career development/growth plans, conducting performance reviews, and 1:1s with team members  - Hands-on experience fine-tuning and training models in-house in your most recent role - Experience working with LLMs, RAG, and embeddings  - Experience deploying trained LLMs to production - Proficiency in Python, PyTorch, and Kubernetes - Strong management and mentorship skills, fostering a collaborative and innovative team culture - Excellent written and oral communication skills with an ability to articulate technical concepts clearly and succinctly - Excellent quantitative critical thinking skills What We Offer - Flexible paid time off (PTO) - Expansive coverage for health, dental, and vision - Employer contribution to Health Savings Accounts (HSA) - Generous parental leave policy - Full employee coverage for life insurance - Home office stipend - Cell phone/internet reimbursement - Company-paid holidays - 401(K) plan Compensation - Based on market data and other factors, the salary range for this position is $230,000 - $310,000 + Equity. However, a salary higher or lower than this range may be appropriate for a candidate whose qualifications differ meaningfully from those listed in the job description. The above represents the expected salary range for this job requisition. Ultimately, in determining your pay, we'll consider your location, experience, and other job-related factors. We’re committed to doing the best work of our lives, together. Come see if we're the right team for you. AKASA is a proud equal opportunity employer and we believe that a diverse and inclusive workforce is an imperative. We welcome people of different backgrounds, genders, races, ethnicities, abilities, sexual orientations, and perspectives, just to name a few. We do not discriminate based upon any protected class and we encourage candidates of all identities and backgrounds to apply. AKASA considers qualified applicants regardless of criminal histories in accordance with the San Francisco Fair Chance Ordinance. [Upgrade to PRO to see link] AKASA is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at [Upgrade to PRO to see contact].