IC1 Machine Learning Engineer
I deliver lots of high quality production-ready code with direction from the team
Area of ownership and level of autonomy / ambiguity
Organizational reach and extent of influence
Technical levers typically exercised to achieve business impact
- I execute on defined tasks and contribute to solving problems with defined solutions.
- I work within the scope of my team with specific guidance from my manager/TL
- Craft - I primarily focus on improving my craft as an engineer
- I work with my manager to prioritize tasks that add the most value and deliver high-quality results for my customer
- I understand and effectively participate in the core processes of my team (planning, on-call rotations, bug triage, metrics review, etc)
- I follow through on my commitments, take responsibility for my work, and deliver my work on time
- I ask questions to clarify expectations
- I own my failures and learn from them
- I escalate to my manager when I get stuck and reflect on ways that I can improve from my mistakes
Agility / Innovation
- I share new ideas and can adapt my work when circumstances change
- I'm open to and act upon feedback from my manager and peers
- I'm gaining self-awareness about my strengths and areas for development
- I have a high standard of excellence for my work
- I am learning to interview and assess candidates to help us build a diverse and talented team. I consistently provide timely, detailed, and evidence-based interview feedback.
- I am able to represent my team’s initiatives and goals to candidates in a compelling way
- I can effectively collaborate to get work done
- I work with my manager to manage conflict with empathy in mind
- I listen to different perspectives and I remove biases from my words and actions
- I practice the Dropbox Diversity Commitments on a regular basis
- I write and speak clearly
- I listen to understand others and ask clarifying questions
- I share relevant information on my project including difficult task-level trade-offs that impact the product to my manager and team (including product/business partners).
I focus on learning the fundamentals of ML and how to apply them to business problems.
- I work on ML models by adapting existing tutorials/guides for new purposes.
- I can analyze and present datasets or results of experiments, with simple methods.
- I apply existing tools and libraries from my team to advance my project.
- I understand the reasoning behind my team’s design decisions to verify and debug implementations of the designs.
- I translate ideas into clear code, written to be read as well as executed
- My code is free of glaring errors - bugs are in edge cases or design, not mainline paths - and is well documented and well tested with appropriate use of manual vs automated tests
- I’m capable of reading and navigating functions and classes/modules that I didn’t write
- I am learning to tackle coding tasks with high throughput while maintaining appropriately high quality; I optimize for either speed or quality, depending on the explicitly stated needs of my team