Career Growth
Level up your AI career — progression roadmaps, salary negotiation and remote work.
Career tracks
Two parallel paths to grow your AI career.
Technical track
Junior ML Engineer (L3)
$80k - $130k0-2 years
- Implement existing ML models
- Write data pipelines
- Run experiments under guidance
- Write clean, tested code
Python, SQLScikit-learn, pandasBasic ML algorithmsGit, testing
Time to next: 2-3 years
ML Engineer (L4)
$130k - $200k2-5 years
- Design and implement ML systems
- Own features end-to-end
- Mentor junior engineers
- Improve model performance
Deep learning frameworks (PyTorch/TensorFlow)Production ML systemsExperiment trackingModel deployment
Time to next: 2-4 years
Senior ML Engineer (L5)
$200k - $350k5-8 years
- Lead major ML initiatives
- Define technical strategy
- Mentor team members
- Make architecture decisions
System designMLOps at scaleTechnical leadershipCross-functional collaboration
Time to next: 3-5 years
Staff ML Engineer (L6)
$300k - $500k+8-12 years
- Set technical direction for org
- Drive critical company initiatives
- Influence product strategy
- Grow engineering talent
Deep technical expertiseStrategic thinkingOrg-level impactMentorship at scale
Time to next: 4-6 years
Principal/Distinguished Engineer (L7+)
$400k - $800k+12+ years
- Company-wide technical leadership
- Industry thought leadership
- Strategic technology bets
- Recruit and grow leaders
Exceptional technical depthVisionary thinkingExternal influenceCompany-level impact
Management track
ML Engineer → Tech Lead
3-5 years
- Lead small team (2-4 people)
- Still write code (50%+ time)
- Make technical decisions
- Mentor team members
+ Project management+ Delegation+ Stakeholder communication+ Basic people management
Engineering Manager
$180k - $300k5-8 years
- Manage team (4-8 people)
- Hiring and performance management
- Career development
- Resource planning
- Less coding (20-30% time)
+ Performance reviews+ Hiring+ Conflict resolution+ Budget management
Senior Engineering Manager / Director
$250k - $450k8-12 years
- Manage managers
- Org-level strategy
- Cross-functional partnerships
- Hiring at scale
VP of Engineering / ML
$350k - $700k+12+ years
- Leadership team
- Company strategy
- Org design
- Executive communication
Specialist tracks
Research Scientist
$150k - $500k+Focus on novel ML research, publishing papers
Employers: Big tech labs, AI startups, universities
Requirements: Often PhD or equivalent research experience
- Cutting-edge work
- Intellectual freedom
- Publication credit
- Fewer jobs
- Competitive
- May be distant from product
MLOps / ML Platform Engineer
$130k - $350kBuild infrastructure for ML teams
Employers: Any company with ML teams
Requirements: Strong systems/infra background + ML knowledge
- High demand
- Enable many ML engineers
- Systems work
- Less ML modeling
- Infrastructure challenges
AI Product Manager
$120k - $350kDefine AI products and features
Employers: AI companies, tech companies with AI products
Requirements: PM experience + strong AI understanding
- Product ownership
- Cross-functional
- Strategic
- Less hands-on technical
- Depends on eng execution
Transition advice
Ic To Manager
- Make sure you actually want to manage (it's different work)
- Start with tech lead role
- Read management books (The Manager's Path, High Output Management)
- Find a manager mentor
- Remember: your job is now to make your team successful
Manager To Ic
- Totally valid - many senior ICs earn more than managers
- Be honest about why you're switching back
- May need to take slight level step back
- Skills are still valuable (communication, planning)
Specialist Transition
- Build skills in the new specialty on the side
- Look for internal transfer opportunities
- Network with people in target specialty
- May need to take title/pay cut initially