Principal Artificial Intelligence Engineer

Innovaccer
San Francisco
Workplace: OnsiteFull timeFunction: Data Science & Machine LearningEducation: bachelorsSkills: ["Curiosity","Experiment design","Analysis","Communication","Mentorship"]

Design, develop, and deploy production-grade AI systems, including LLM-based solutions, AI agents, RAG, and intelligent automation workflows. Take models from experimentation and prototyping through production deployment and optimization, owning model accuracy, latency, and evaluation. Build and debug training/serving pipelines using PyTorch and distributed training, and communicate results to clinicians and operators while helping guide the team’s technical direction.

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FursaFursa
Innovaccer
Innovaccer
1 day ago

Principal Artificial Intelligence Engineer

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Source: Company careers pageValidated by: Fursa AI
Last checked: 9 hours agoStatus: Live

Job Summary

Design, develop, and deploy production-grade AI systems, including LLM-based solutions, AI agents, RAG, and intelligent automation workflows. Take models from experimentation and prototyping through production deployment and optimization, owning model accuracy, latency, and evaluation. Build and debug training/serving pipelines using PyTorch and distributed training, and communicate results to clinicians and operators while helping guide the team’s technical direction.
Location: San Francisco
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Sr. Manager level

Key Responsibilities

  • •Design, develop, and deploy AI-powered applications including LLM solutions, AI agents, RAG, and automation workflows.
  • •Build real product model layers: choose model sizes, compose multiple models into working systems, and meet production accuracy and latency bars.
  • •Run and evaluate experiments end-to-end, including hypothesis/ablation work and building evaluation to challenge overly optimistic results.
  • •Own large-scale training and post-training production readiness, including diagnosing what broke and improving operational discipline.
  • •Set technical direction and potentially mentor engineers as the team grows, translating ambiguous problems into plans and execution tasks.

Pay and Benefits

Perks:Paid LeaveParental LeaveHealth InsuranceDentalVisionDisabilityLife InsurancePet Insurance

Key Requirements

  • •MS or PhD in Computer Science, Machine Learning, or a related quantitative field; exceptional BS candidates with substantial research or open-source work may be considered.
  • •First-author publications at NeurIPS, ICML, ICLR, ACL, EMNLP (or similar), meaningful open-source ML contributions, and/or models shipped that people actually used.
  • •Experience fine-tuning an open-weight model, understanding parameter-efficient vs full fine-tuning, and being able to explain the choice.
  • •Strong Python and PyTorch with familiarity in training and serving stacks such as HuggingFace, FSDP/DeepSpeed, and vLLM/SGLang (or equivalents).
  • •Hands-on multi-GPU and multi-node training experience, including sharding strategy knowledge and evidence of models running in production.
Experience:Open sourceAILLM
Education:Bachelor's
Skills:CuriosityExperiment designAnalysisCommunicationMentorship
Tech Stack:PythonPyTorchLLMAI agentsRetrieval-Augmented Generation (RAG)HuggingFaceFSDPDeepSpeedVLLMSGLangMulti-GPU trainingShardingDistributed trainingFine-tuningData pipelinesEvaluation (evals)

Company Brief

Innovaccer
Provides a healthcare data activation platform that unifies clinical, claims, and operational data to enable analytics, care management, population health, and value-based care initiatives for providers, payers, and life sciences organizations.
Industry: HealthTech
Company Size: Enterprise (1,001+ employees)
Growth: Scaleup
Valuation: Unicorn (USD 1B+)
Funding: Series D
Headquarters: San Francisco, United States
Founded: 2014
WebsiteLinkedIn