[HN Gopher] Ask HN: What does an ML Engineer do?
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Ask HN: What does an ML Engineer do?
I have a few years of experience as an ML Engineer, however I
recently changed jobs and I was shocked to learn that my new
employer has a very different job definition for ML Engineer than
the one I was familiar with. I _thought_ that the standard
definition of an ML Engineer is an engineer who specializes in
building machine learning models, essentially a subtype of a data
scientist. At my new company, an ML Engineer is someone who
supports ML models but never works on machine learning directly. At
this new company, ML Engineers are Data Engineers who support
machine learning applications. What is the generally accepted
definition of an ML Engineer?
Author : chroem-
Score : 8 points
Date : 2021-06-18 21:02 UTC (1 hours ago)
| malux85 wrote:
| I would say, some combinations of:
|
| - Helping with feature engineering at scale
|
| - Putting models into production
|
| - All of the environmental stuff (Framework versions, security
| patching, etc)
|
| - Monitoring models and model drift
|
| - Supporting hot/swapping models with zero downtime
|
| - Model persistence, A/B testing and evaluation in production
|
| - Distributed hyperparameter tuning
| MattGaiser wrote:
| I work for a company where half the company consists of ML
| Developers. They match your definition. Your job is what we call
| ML Ops.
|
| Kind of interested how you got hired to a completely different
| role though and how that didn't come up in the interview.
| kajecounterhack wrote:
| I think it depends on the company. In my experience most
| companies have it halfway between the things you described (some
| data engineering + some modeling). Companies with less
| established infra generally have more data engineering work.
|
| Imo unless you are a rich company or have a well funded research
| arm, it mostly seems wasteful to make someone's job pure
| modeling.
| sohei wrote:
| > I was shocked to learn that my new employer has a very
| different job definition for ML Engineer than the one I was
| familiar with.
|
| Job titles do not have consistent meaning across regions or
| industries. People use buzzwords and hype to recruit funding and
| talent.
|
| You've learned an important lesson: use interviews to gather
| information about companies and teams. "Can you describe in broad
| strokes a typical project for this role?" is a perfectly
| reasonable question to ask a hiring manager.
| travisjungroth wrote:
| How did you get through a job description and the interview
| process without this coming up? Was it a bait and switch?
| toomuchtodo wrote:
| Sounds like their title for the job should've been ML Infra or ML
| DevOps engineer to indicate it's a supporting role versus a
| primary practitioner. Annoying, sorry OP.
| sedeki wrote:
| My subjective view coincides with your new employer. I think
| that's pretty common.
|
| ML Scientist and Data Scientist versus ML Engineer and Data
| Engineer.
| pmalynin wrote:
| Its whatever you want it to be, which is the greatest thing.
|
| Ex ML Engineer at a company.
| wodenokoto wrote:
| I'd say what you've mentioned are the 2 typical definitions.
|
| Either its an expert at building and training ml models, or its
| an expert at putting ml models in production.
| benrawk wrote:
| Yeah I think in general "ML engineers" are building models (can
| include feature engineering) and then deploying them into
| production.
| discordance wrote:
| We call that role ML Ops at our work. It's a mix of data eng and
| dev ops.
| [deleted]
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