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Manager, Machine Learning - Applied AI

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What you’ll work on

Full posting
  • Own multi-track ML project plans from scoping to delivery, including risks and dependencies

  • Run sprint planning, stand-ups, demos and executive readouts with decision logs

  • Align Product, Engineering, Clinical and Customer teams on priorities and unblock work

  • Establish evaluation frameworks for LLM/RAG and clinical NLP systems

  • Mentor ML engineers and data scientists with clear expectations and growth paths

From the employer’s posting
Own the multi‑track plan for ML projects (scoping → delivery), including timelines, dependencies, resources, and risk/RAID management.
Run the operating rhythm: backlog/roadmap, sprint planning, stand‑ups, demos, and executive readouts with crisp status and decision logs.
Align Product, Engineering, Clinical, and Customer teams around priorities; drive decisions and unblock fast.
Establish evaluation frameworks for LLM/RAG and clinical NLP (offline metrics, red‑teaming, human‑in‑the‑loop QA).
Mentor ML engineers/data scientists; set clear expectations, feedback loops, and growth paths.

About Autonomize

Autonomize AI is revolutionizing healthcare by streamlining knowledge workflows with AI.

In the employer’s words · Read in context

Apply at Autonomize

Posting record

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Actively hiringFirst seen by us 5 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Oct 29, 20265 days ago
Recorded sightings
7
Last seen by us
Nov 4, 2026
Employer says posted
Oct 27, 2026

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How this job compares

Time since we first saw it

Day 5

Early. Similar jobs usually come down between day 7 and day 53.

From 7,814 similar postings that came down. Coming down is not always a hire.

Autonomize is hiring

2 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • PyTorch
  • TensorFlow
Where the posting names them
- Strong program management fundamentals (road‑mapping, 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.

Your next step

Complete your application on autonomize.keka.com. The employer’s form will show what is required.

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About the role

We file this job under Data Leadership, by the work the posting describes.

Data leaders run data teams or design how a company's data fits together. Managers hire, set priorities and answer for whether the data work pays off; architects choose the systems and the shape of the data.

Expect years of hands-on data work, experience leading people or projects, and the ability to explain tradeoffs to executives.

Unlike a senior engineer or analyst, most of a data leader's week goes to people, planning and decisions rather than building.

US government figures for computer and information systems managers

Median yearly pay, May 2025
$175,140
Expected change, 2025 to 2035
15.8% more jobsagainst 3.5% for all jobs

The government has no code for data leaders, so these figures are for the closest group, computer and information systems managers, which includes data processing and data operations managers.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 11-3021.

Job description

View original posting ↗

  • Please note: This is a 100% onsite position located in Bangalore, India. Kindly apply only if you are willing and able to work on-site from our Bangalore office.
  • Office address (Bangalore) : HM Eleganza, 31 & 31/1, Museum Rd, near Church Street, Shanthala Nagar, Ashok Nagar, Bengaluru, Karnataka 560001

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 Manager, Machine Learning Engineer - Applied AI to program‑manage a portfolio of ML initiatives—from LLM/RAG workflows to clinical NLP and MLOps. You’ll create clarity in ambiguity, orchestrate cross‑functional execution, and own outcomes end‑to‑end. 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 multi‑track plan for ML projects (scoping → delivery), including timelines, dependencies, resources, and risk/RAID management.

  • Run the operating rhythm: backlog/roadmap, sprint planning, stand‑ups, 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.

Cross‑Functional 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 production‑ready ML with reliability.

Technical Depth & MLOps

  • Review designs/PRDs, sanity‑check 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, red‑teaming, human‑in‑the‑loop 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


  • 10+ years in Applied ML/DS/AI (or ML‑heavy product/engineering), including 5+ years leading multi‑workstream ML programs or teams.

  • Proven track record shipping ML/LLM systems to production with clear business outcomes.

  • Strong program management fundamentals (road‑mapping, 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.

What Will Make You Stand Out


  • Experience with RAG pipelines, clinical NLP (e.g., de‑identification, 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.


Source details

View original posting ↗

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Pay

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Location & working pattern

Bengaluru, KA, India

- Please note: This is a 100% onsite position located in Bangalore, India. Kindly apply only if you are willing and able to work on-site from our Bangalore office. - Office address (Bangalore) : HM Eleganza, 31 & 31/1, Museum Rd, near Church Street, Shanthala Nagar, Ashok Nagar, Bengaluru, Karnataka 560001
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