AKASA
Sr. Software Engineer, Client Solutions
New York City, New York, United States · Senior
Sponsorship not specified$150k-$200kDetected 13 days ago
PythonReactFastAPIGitDockerKubernetesCI/CDMachine LearningData EngineeringLLMsHL7/FHIRResearchCommunication
About the role
- You will work on the lifecycle and deployment of the ML models that power our products.
- You'll work closely with client engagement, product, and R&D teams to ensure smooth deployments, ongoing production stability and expansion of our deployment platform.
Responsibilities
- Build and own evaluation frameworks to continuously measure and improve LLM performance across customer deployments
- Work closely with R&D engineering teams to build robust scalable client solutions
Requirements
- Bachelor's degree in Computer Science, Engineering, or similar
- Proficiency in Docker, Kubernetes, AWS.
- CI/CD experience with GitHub Actions.
Compensation
- Based on market data and other factors, the salary range for this position is $150,000-$200,000 + 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.
- IC4 base salary range is 150-175k, IC5 is 175k-200k
- The above represents the expected salary range for this job requisition.
Benefits
- 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
- Based on market data and other factors, the salary range for this position is $150,000-$200,000 + Equity.
Company info
- Work with client engagement teams to guide customers through technical onboarding, integration setup, troubleshooting, and data acquisition
Equal opportunity
- equal opportunity employer and we believe that a diverse and inclusive workforce is an imperative.
This listing is sourced directly from AKASA's careers page and normalized into a canonical job model.