Autonomize Inc
About Autonomize AI
Autonomize AI is revolutionizing healthcare by streamlining knowledge workflows with AI. We reduce administrative burdens and elevate outcomes, empowering professionals to focus on what truly matters - improving lives. We're growing fast and looking for bold, driven teammates to join us.
The Opportunity
We're hiring an
Applied ML Manager
to
programmanage a portfolio of ML initiatives -from LLM/RAG workflows to clinical NLP and MLOps. You'll create clarity in ambiguity, orchestrate crossfunctional execution, and own outcomes endtoend. This role is perfect for a technical program/people leader who can
go deep on the work
while
driving scale -a
driver, not a passenger -and who thrives on aligning fast and executing faster.
Key Responsibilities
Program & Portfolio Leadership
Own the multitrack plan for ML projects (scoping delivery), including timelines, dependencies, resources, and risk/RAID management. Run the operating rhythm: backlog/roadmap, sprint planning, standups, demos, and executive readouts with crisp status and decision logs. Define success criteria and measurable outcomes (quality, latency, cost, safety), then track and improve them. CrossFunctional Execution
Align Product, Engineering, Clinical, and Customer teams around priorities; drive decisions and unblock fast. Translate ambiguous problem statements into clear problem definitions, milestones, and acceptance criteria. Coordinate data pipelines, annotations, experimentation, and evaluation-shipping productionready ML with reliability. Technical Depth & MLOps
Review designs/PRDs, sanitycheck experiments, and dive into notebooks or dashboards to resolve issues when needed. Partner on MLOps best practices (versioning, CI/CD for models, observability, guardrails, rollback plans). Establish evaluation frameworks for LLM/RAG and clinical NLP (offline metrics, redteaming, humanintheloop QA). People & Scale
Mentor ML engineers/data scientists; set clear expectations, feedback loops, and growth paths. Improve the system-templates, playbooks, runbooks, postmortems-to compound team impact as we scale.
Must-Have Qualifications
6+ years in Applied ML/DS/AI (or MLheavy product/engineering), including 2+ years leading
multiworkstream
ML programs or teams. Proven track record shipping ML/LLM systems to production with clear business outcomes. Strong program management fundamentals (roadmapping, risk management, stakeholder alignment) and excellent written/verbal communication. Working knowledge of modern ML/LLM tooling (Python, PyTorch/TensorFlow, experiment tracking, data/feature stores, eval frameworks, model observability). Ability to
operate in the final mile -closing loops with high judgment, urgency, and attention to detail. Healthcare curiosity and comfort with privacy, safety, and compliance considerations.
Bonus
Experience with RAG pipelines, clinical NLP (e.g., deidentification, coding, entity linking), or payer/provider workflows. Background building MLOps platforms or evaluation harnesses for LLMs. Experience mentoring/hiring ML talent and leading vendors/partners. What we offer
A chance to make a real impact in the future of healthcare Autonomy, ownership, and the ability to chart your own growth path Competitive compensation and benefits 100% employer-paid health, vision, and dental insurance Retirement plans (401k), disability insurance, employee assistance programs
How to Apply
Please submit your resume and a brief cover letter to careers@autonomize.ai explaining why you are the ideal candidate for this role. We are excited to meet someone who is eager to bring their skills, enthusiasm, and creativity to our team!
Autonomize AI is revolutionizing healthcare by streamlining knowledge workflows with AI. We reduce administrative burdens and elevate outcomes, empowering professionals to focus on what truly matters - improving lives. We're growing fast and looking for bold, driven teammates to join us.
The Opportunity
We're hiring an
Applied ML Manager
to
programmanage a portfolio of ML initiatives -from LLM/RAG workflows to clinical NLP and MLOps. You'll create clarity in ambiguity, orchestrate crossfunctional execution, and own outcomes endtoend. This role is perfect for a technical program/people leader who can
go deep on the work
while
driving scale -a
driver, not a passenger -and who thrives on aligning fast and executing faster.
Key Responsibilities
Program & Portfolio Leadership
Own the multitrack plan for ML projects (scoping delivery), including timelines, dependencies, resources, and risk/RAID management. Run the operating rhythm: backlog/roadmap, sprint planning, standups, demos, and executive readouts with crisp status and decision logs. Define success criteria and measurable outcomes (quality, latency, cost, safety), then track and improve them. CrossFunctional Execution
Align Product, Engineering, Clinical, and Customer teams around priorities; drive decisions and unblock fast. Translate ambiguous problem statements into clear problem definitions, milestones, and acceptance criteria. Coordinate data pipelines, annotations, experimentation, and evaluation-shipping productionready ML with reliability. Technical Depth & MLOps
Review designs/PRDs, sanitycheck experiments, and dive into notebooks or dashboards to resolve issues when needed. Partner on MLOps best practices (versioning, CI/CD for models, observability, guardrails, rollback plans). Establish evaluation frameworks for LLM/RAG and clinical NLP (offline metrics, redteaming, humanintheloop QA). People & Scale
Mentor ML engineers/data scientists; set clear expectations, feedback loops, and growth paths. Improve the system-templates, playbooks, runbooks, postmortems-to compound team impact as we scale.
Must-Have Qualifications
6+ years in Applied ML/DS/AI (or MLheavy product/engineering), including 2+ years leading
multiworkstream
ML programs or teams. Proven track record shipping ML/LLM systems to production with clear business outcomes. Strong program management fundamentals (roadmapping, risk management, stakeholder alignment) and excellent written/verbal communication. Working knowledge of modern ML/LLM tooling (Python, PyTorch/TensorFlow, experiment tracking, data/feature stores, eval frameworks, model observability). Ability to
operate in the final mile -closing loops with high judgment, urgency, and attention to detail. Healthcare curiosity and comfort with privacy, safety, and compliance considerations.
Bonus
Experience with RAG pipelines, clinical NLP (e.g., deidentification, coding, entity linking), or payer/provider workflows. Background building MLOps platforms or evaluation harnesses for LLMs. Experience mentoring/hiring ML talent and leading vendors/partners. What we offer
A chance to make a real impact in the future of healthcare Autonomy, ownership, and the ability to chart your own growth path Competitive compensation and benefits 100% employer-paid health, vision, and dental insurance Retirement plans (401k), disability insurance, employee assistance programs
How to Apply
Please submit your resume and a brief cover letter to careers@autonomize.ai explaining why you are the ideal candidate for this role. We are excited to meet someone who is eager to bring their skills, enthusiasm, and creativity to our team!