Sr. Machine Learning Researcher

About AKASA

Our mission is to enable human health.

AKASA is the leading developer of AI for healthcare operations. Founded in 2019 AKASA has raised $85M in funding.

Our founding team includes Silicon Valley leaders who have founded or been founding team members of multiple companies with successful exits. Our investors include Andreessen Horowitz BOND and Costanoa Ventures among others. Recognized in 2021 among Top 150 “Most Innovative Digital Health Startups” by CB Insights Top 75 “Best Places to Work” by Modern Healthcare Certified as a “Great Place to Work” two years in a row and ranked #34 of Top 100 Healthcare Companies in 2021 by The Healthcare Technology Report. Learn more at www.AKASA.com .

We are building the future of healthcare with AI.  Everyone is welcome — as an inclusive workplace our employees are comfortable bringing their authentic selves to work.

Join us.

About the Role

As a remote Sr. Machine Learning Researcher you'll report to our CTO and work with a team of talented engineers from top schools who have professional experience with leading companies. You will partner closely with a strong team of PhD Researchers and Machine Learning Engineers.

AKASA is based in South San Francisco. As a company we embraced remote work. We consider ourselves experts in working collaboratively wherever our team members reside.

What You'll Do

• Train or Fine-Tune Large Language Models (e.g. Llama architecture) for Healthcare Applications

• Create innovative AI/ML solutions to address real-world human health and healthcare problems

• Keep up to date with the technological improvements within the AI/ML community and decide when those developments warrant incorporation

Skills & Qualifications

• Professional experience with training Large Language Models

• Experience working with healthcare data (e.g. EDI FHIR)

• A passion for working on important and impactful human health and healthcare problems

• Ph.D. or equivalent industry experience related to AI computer vision natural language processing computational neuroscience optimization computer science statistics applied mathematics or data science.

• Publications at peer-reviewed AI conferences (e.g. NeurIPS ICML ICLR CVPR ICCV ECCV ACL NAACL and EMNLP) are preferred.

• Experience in rapid prototyping and quick experimentation and proficiency in writing code that others can understand adapt and extend

• Ability to multitask effectively under pressure and quickly adapt within a fast-paced environment with strong written and verbal communication skills

What We Offer

• Unlimited 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

• Company-paid holidays

• 401(K) plan

Compensation

• Based on market data and other factors the salary range for this position is $175000-$230000 + 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.

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 [email protected].