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機械学習エンジニアの英会話

Posted at

◆ 1. 出社・雑談(Warm-up Talk)

シチュエーション 英語フレーズ 日本語訳
挨拶・開始 Morning! Ready to debug the universe? おはよう、さあデバッグの時間だね
気軽に近況を聞く What’s keeping you busy these days? 最近何やってるの?
体調を気づかう You look a bit tired. Long night training models? 少し疲れてるみたいだね。モデルの訓練で夜更かし?
天気系 It's perfect weather to stay inside and code. 引きこもってコード書くのに最高の天気だね

◆ 2. 開発に関する会話(Technical Chit-chat)

シチュエーション 英語フレーズ 日本語訳
フレームワーク Are you using TensorFlow or PyTorch for this one? これ、TensorFlow?PyTorch?
実装 I'm trying to fine-tune a model on our dataset. データセットでモデルをファインチューニング中
ハイパーパラメータ I might try lowering the learning rate. 学習率を下げてみようかな
エラー I hit a weird bug in the data pipeline. データパイプラインで変なバグに当たった
実行環境 Is this running locally or on the cloud? これ、ローカル?クラウド?
デバッグ Let’s check the logs to see what's going wrong. ログ見て原因探そう

◆ 3. 会議・報告(Meetings & Stand-ups)

シチュエーション 英語フレーズ 日本語訳
進捗報告 I’ve made progress on the data preprocessing pipeline. データ前処理パイプラインを進めました
問題報告 I'm still stuck on model convergence. モデルの収束で詰まってます
質問する Could you clarify what you mean by “alignment loss”? 「アライメント損失」ってどういう意味ですか?
賛同・提案 That makes sense. How about trying a simpler model first? それは理解できる。まずは単純なモデルで試してみるのは?
締め Let’s circle back once we have some results. 結果が出たらまた話しましょう

◆ 4. Slack・チャットでの表現(Async Communication)

シチュエーション 英語フレーズ 日本語訳
軽く聞く Quick question: is the repo up to date? ちょっと質問:リポジトリは最新?
調査中 Looking into it now. I’ll update you shortly. 今調べてます。すぐ連絡します
提案 Maybe we should re-train with a larger batch size. バッチサイズ大きくして再学習するのもありかも
応答 Got it, thanks! That explains it. 了解、ありがとう!納得です
終了 Let me know if you need anything else. 何かあれば言ってください

◆ 5. コードレビューやGitHubコメント

シチュエーション 英語フレーズ 日本語訳
修正依頼 Could you add a comment here for clarity? ここに説明コメント入れてくれる?
気づき指摘 This might break for edge cases. これ、境界ケースで壊れるかも
提案 Maybe extract this into a separate function. 別関数に切り出してもいいかも
承認 Looks good to me. Thanks! 問題なさそうです、ありがとう!
謝意 Appreciate the quick fix! 素早い修正感謝です!

◆ 6. 発表・プレゼン(技術発表)

シチュエーション 英語フレーズ 日本語訳
スタート Today I’ll talk about our approach to fine-tuning BERT. 今日はBERTファインチューニングの手法について話します
図の説明 As you can see in this chart, accuracy improves after 10 epochs. この図から分かるように、10エポック後に精度が上がります
言い換え In other words, our method generalizes better. 言い換えると、我々の手法は汎化性能が高いです
終わり That’s all for my presentation. I’m happy to take questions. 発表は以上です。ご質問どうぞ

◆ 応用:役立つ決まり文句セット(汎用フレーズ)

用途 英語フレーズ
相づち I see. / That makes sense. / Gotcha.
提案 How about we try...? / What if we...?
質問 Could you elaborate on that? / What do you mean by...?
同意・反対 I agree. / I’m not sure I agree with that.
話を戻す Anyway, back to the main topic...

◆ 基本テンプレート(初級者向け)

Hi, my name is [Your Name].  
I'm a machine learning engineer.  
I mainly work on data preprocessing and building models using Python.  
Recently, I've been working on a classification problem using scikit-learn.  
Nice to meet you!

◆ 応用テンプレート(中級者向け)

Hello, I'm [Your Name], a machine learning engineer with a background in [your background, e.g. computer science].  
I specialize in model development, especially in NLP and time series forecasting.  
My main tech stack includes Python, PyTorch, and MLflow.  
Currently, I'm working on deploying ML models to production using Docker and FastAPI.  
I'm always excited to learn about new algorithms and real-world applications.  
Looking forward to collaborating with you.

◆ 面接や国際会議向け(上級者向け)

Hi, I'm [Your Name]. I work as a machine learning engineer focusing on end-to-end ML pipelines.  
I have experience in designing and deploying deep learning models, particularly in computer vision and recommender systems.  
My expertise includes model optimization, experiment tracking, and MLOps practices.  
I’ve recently led a project involving transformer-based architectures for document classification.  
I'm passionate about building scalable systems and contributing to open-source when possible.  
It’s a pleasure to be here and I’d love to exchange ideas with you all.

◆ 中級テンプレート(あなたの情報に差し替えて使用)

Hi, I'm [Your Name], originally from [Your Hometown].

I studied [Your Major] at [Your University], where I got interested in machine learning and data analysis.

Now I work as a machine learning engineer at [Company Name], focusing on [Your Work, e.g., building models, improving performance, etc.].

In my free time, I enjoy [Your Hobby 1] and [Your Hobby 2].

Nice to meet you and I look forward to working with you.

◆ 例文(サンプル)

Hi, I'm Takashi Yamada, originally from Fukuoka.

I studied information science at Kyushu University, where I got interested in machine learning and statistics.

Now I work as a machine learning engineer at TechVision, focusing on model development and real-time inference optimization.

In my free time, I enjoy playing chess and watching sci-fi movies.

Nice to meet you and I look forward to working with you.
Hello. My name is Takashi Yamada.  
I am from Fukuoka, Japan.

I studied computer science at Kyushu University.  
There, I started to like machine learning and data.

Now, I work at a company called TechVision.  
I am a machine learning engineer.  
I make models and try to make them better.

In my free time, I enjoy playing chess and watching science fiction movies.

Nice to meet you. I want to work well with you.

◆ 1. あいさつ・自己紹介のあとに

英語:

Where are you from?  
What kind of work do you do?  
Do you like your job?  

日本語訳:
どちらの出身ですか?
どんなお仕事ですか?
お仕事は好きですか?


◆ 2. 仕事のことを話す

英語:

I work with machine learning models.  
I use Python every day.  
Now I am working on a new project.  
Sometimes it is hard, but I enjoy it.  

日本語訳:
私は機械学習モデルを使って仕事をしています。
毎日Pythonを使います。
今は新しいプロジェクトに取り組んでいます。
ときどき難しいですが、楽しいです。


◆ 3. 相手に質問する(シンプル)

英語:

What tools do you use?  
Do you like coding?  
How long have you been doing this job?  

日本語訳:
どんなツールを使っていますか?
プログラミングは好きですか?
この仕事はどれくらいやっていますか?


◆ 4. 雑談・趣味の話

英語:

What do you do in your free time?  
I like reading and walking.  
Do you play any games?  

日本語訳:
自由な時間は何をしますか?
私は読書と散歩が好きです。
ゲームはしますか?


◆ 5. 簡単なリアクション

英語 日本語訳
That’s great! それはいいですね!
I see. なるほど。
Sounds fun! 楽しそうですね!
Me too. 私もです。
Really? 本当ですか?

使い方例(会話シミュレーション):

A: What are you working on now?
B: I’m working on a model for image classification.
A: Sounds interesting! Do you use PyTorch?
B: Yes. I like PyTorch because it’s simple.

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