I’m good at at least three things, derived from 14+ years working at the intersection of software and linguistics:

• Natural language processing – I am fluent with the tools and practices used to automatically infer structured, machine-consumable information from the noisiness and surprises of natural language, whether written or derived from speech.
• Machine learning and statistical methods – I do not fear the occasional outlier, and I am well equipped to put concrete bounds on what occasional means. I work with real data, and I prefer to have concrete evaluation measures; when necessary, I will implement my own.
• Software engineering and aesthetics – I am good at software design, and I enjoy the puzzle of building research infrastructure: how do you build a boat to sail where no one has sailed before? I understand not only the tools of NLP and machine-learning, but how to structure (and restructure) shared architectures so that engineers and scientists can cooperate smoothly.

I’ve been working on all three of these since about 1998; my PhD is –effectively– in all three. I’ve started interviewing around the Puget Sound area — but of course I’d welcome any other local leads.

Dearest creature in creation,
Study English pronunciation.
I will teach you in my verse
Sounds like corpse, corps, horse, and worse.
I will keep you, Suzy, busy,
Make your head with heat grow dizzy.

It goes on for 112 lines. There are a few that I only got right by the skin of my rhyme scheme and a bloody-minded adherence to the poem’s local meter, even when I knew the words’ meanings:

Hear me say, devoid of trickery,
Daughter, laughter, and Terpsichore[...]
Gertrude, German, wind and mind,
Scene, Melpomene, mankind.

…a penchant for reading Greek mythology as a kid goes a long way — I knew that Terpsichore was the muse of dance — but D’Aulaires doesn’t tell you that “Terpsichore” rhymes with “trickery”. A few others I whiffed on (viscount, Balmoral) are inkhorn terms to me, largely because I’ve only ever read them in period pieces from the east side of the Atlantic.

The link’s framing text claims, suspiciously, that

If you can pronounce correctly every word in this poem, you will be speaking English better than 90% of the native English speakers in the world.

… which triggered my “lazy writer’s bad statistics” alarm: I couldn’t get all of them right, and I have empirical evidence (what, the GRE isn’t empirical?) that my mastery of English sesquipedaliana is in the 99th percentile. The subsequent citation to “a Frenchman” further suggests that the framing author is just looking for some catchy-sounding but un-accountable numbers (N words for snow?) to spice up the writing.