AI/ML Engineering - Remote
About the Company
Vida is a virtual, personalized obesity care provider that uses evidence-based treatment to help people manage obesity and related conditions, including diabetes, high blood pressure, anxiety, and depression. Its care teams include Obesity Medicine-Certified Physicians, Registered Dietitians, Expert Coaches, and Licensed Therapists who take a whole-person approach to improving health and well-being. By combining healthcare expertise with advanced technology, Vida works to make quality care more accessible. The company partners with Fortune 100 companies, national health insurers, and large healthcare providers to help people improve their health.
About the Role
Vida is rebuilding its technology data platform to strengthen patient data protection, improve data governance, and support self-service analytics. As part of this work, the company is seeking an experienced AI/ML and Software Engineering professional to help build the infrastructure needed to support future artificial intelligence and machine learning capabilities. This hands-on role spans software engineering, data infrastructure, cloud platforms, DevOps, security, and production AI/ML systems. You will work with platform, security, and DevOps teams to develop reliable, scalable systems while ensuring sensitive health information remains protected. You will also help establish technical standards and practices that enable the safe integration of AI and machine learning into Vida's products and operations.
Key Responsibilities
Contribute to the development of the data platform, including data ingestion, transformation, canonical data models, entity resolution, event infrastructure, configuration as code, APIs, and serving layers. Improve DevOps practices and system reliability through CI/CD, infrastructure as code, environment management, and observability across metrics, logs, traces, and service-level objectives. Partner with Security and IT teams to implement data classification, access controls, secrets management, key management, and safeguards aligned with HIPAA and HITRUST. Build the foundations of the AI/ML platform, including model serving, inference gateways, feature and training data pipelines, and model lifecycle management. Support model registration, evaluation, deployment, and monitoring to enable reliable production machine learning. Integrate large language models (LLMs) with appropriate grounding, evaluation, and guardrails. Keep protected health information within controlled boundaries and use in-VPC or local inference when required to prevent sensitive data exposure. Work alongside existing team leads to strengthen AI and ML knowledge across platform, security, and DevOps teams. Establish reusable technical patterns and practices that other teams can build on. Take on additional responsibilities as needed.
Required Qualifications
Bachelor's degree or higher. 7–10+ years of experience building and scaling production-grade machine learning or AI systems. Demonstrated experience as a generalist Software Engineer across backend development, infrastructure, and data engineering. Substantial hands-on experience building and deploying production AI/ML systems, including MLOps, model serving, inference infrastructure, feature and data pipelines, and model integration into real applications. Strong cloud platform experience, ideally with Google Cloud services such as Vertex AI, BigQuery, Cloud Run, Pub/Sub, Cloud SQL, and Google Kubernetes Engine (GKE). Experience with equivalent AWS or Azure services is also welcome. Experience with CI/CD, Terraform or similar infrastructure-as-code tools, containers, Kubernetes, and production observability. Solid data engineering skills, including SQL, pipeline tooling such as dbt, and data warehousing. A security-focused mindset and the ability to work with sensitive data in regulated environments. Experience with LLM applications, including retrieval, evaluation, guardrails, and knowledge graphs. Ability to work through ambiguity, deliver solutions, and move effectively across different areas of the technology stack.
Preferred Qualifications
Experience with entity resolution or master data management. Experience in healthcare or another regulated data environment. Experience with GraphQL or a federated serving layer. Familiarity with privacy-enhancing technologies. Knowledge of HIPAA or HITRUST requirements is an advantage. Salary and Benefits Annual salary range: $250,000–$275,000. Work Arrangement and Employment Details Work arrangement: Remote. Location eligibility: Employees must reside in and work from the United States, in a state where Vida is authorized to conduct business. International work is not permitted. Work authorization: Applicants must be authorized to work in the United States. Vida does not sponsor work visas for this position. Job postings remain open through the end of the year until the position is filled. Equal Employment Opportunity Vida is an Equal Employment Opportunity and Affirmative Action employer. All qualified applicants receive consideration without regard to race, color, ancestry, religion, gender, gender identity or expression, sexual orientation, marital status, national origin, genetics, disability, age, or veteran status. Vida also considers qualified applicants with criminal histories in accordance with applicable federal, state, and local laws. Vida is committed to recruiting, developing, and retaining a diverse workforce and providing reasonable accommodations for qualified individuals with disabilities and disabled veterans during the application process. Recruitment and Application Notice Vida does not accept unsolicited assistance from headhunters or recruitment firms. Resumes or profiles submitted without a valid, signed search agreement for the specific position become Vida's property, and no recruitment fee will be paid if a candidate is hired through an unsolicited referral. Vida may use AI tools to assist with parts of the hiring process, including reviewing applications, analyzing resumes, and identifying potential inconsistencies or verification signals. These tools support the recruitment team but do not replace human judgment. Final hiring decisions are made by people. Applicants seeking more information about how their data is processed may contact Vida.