Senior Artificial Intelligence Engineer

Innovaccer
San Francisco
Workplace: OnsiteFull timeFunction: Data Science & Machine LearningEducation: bachelorsSkills: ["Hands-on","Curiosity","Problem-solving","Communication","Mentoring"]

Build production-grade AI systems that solve complex problems at scale, working with product, engineering, and data teams. Design, develop, and deploy LLM-based solutions, AI agents, retrieval-augmented generation (RAG), and intelligent automation workflows. Take models from experimentation and prototyping through deployment and optimization, including model/accuracy and evaluation rigor, multi-GPU and multi-node training, and robust data pipelines.

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FursaFursa
Innovaccer
Innovaccer
1 day ago

Senior Artificial Intelligence Engineer

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

Job Summary

Build production-grade AI systems that solve complex problems at scale, working with product, engineering, and data teams. Design, develop, and deploy LLM-based solutions, AI agents, retrieval-augmented generation (RAG), and intelligent automation workflows. Take models from experimentation and prototyping through deployment and optimization, including model/accuracy and evaluation rigor, multi-GPU and multi-node training, and robust data pipelines.
Location: San Francisco
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Develop production-grade AI applications and workflows using LLM-based solutions, AI agents, RAG, and intelligent automation.
  • •Own the model layer for product features, including selecting model sizes, composing models into working systems, and meeting accuracy/latency requirements.
  • •Build evaluation and measurement processes, including designing experiments with hypotheses and ablation to validate results.
  • •Implement and optimize training and serving pipelines, including multi-GPU/multi-node runs and post-training production reliability.
  • •Communicate technical work to non-AI stakeholders (including clinicians and operators) and incorporate feedback to improve output quality.

Pay and Benefits

Perks:Paid LeaveParental LeaveMedicalDentalVisionDisability InsuranceLife InsurancePet InsuranceLegal AidDiscounted Legal

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 are considered.
  • •First-author publications (NeurIPS, ICML, ICLR, ACL, EMNLP, or similar) or meaningful open-source ML contributions, research internships, or models trained and shipped that are used.
  • •Experience fine-tuning open-weight models and understanding parameter-efficient vs full fine-tuning, with the ability to justify tradeoffs.
  • •Strong Python and PyTorch, plus familiarity with training/serving stacks such as HuggingFace, FSDP/DeepSpeed, and vLLM/SGLang (or equivalents).
  • •Hands-on multi-GPU and multi-node training experience, including sharding strategy, production post-training, and building data pipelines for real training runs.
Experience:HealthcareArtificial intelligenceMachine learningLLMOpen source
Education:Bachelor's
Skills:Hands-onCuriosityProblem-solvingCommunicationMentoring
Tech Stack:PythonPyTorchLLMRAGHuggingFaceFSDPDeepSpeedVLLMSGLangMulti-GPU trainingMulti-node trainingSharding

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