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Open nowPosted 133 days ago

Senior ML Engineer - talent pool

RITS128 open roles

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Your applicationOpen nowSenior ML Engineer - talent poolRITS

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on RITS's own form.

The reply lands in your private mailbox

3×more interviews than doing it yourself with ChatGPT.

The clock on this job

Early applications get read.

11.5% of postings close within 7 days. Measured by our own scanner across the market. RITS postings stay open a median of 1 days.

Share of postings closed within
  1. 2.0%1 day
  2. 4.3%3 days
  3. 11.5%7 days
  4. 18.1%14 days
  5. 35.6%30 days
  6. 44.6%60 days
This job: posted 133 days ago

RITS median: 1 days open

The posting

RITS Group to firma informatyczna, która oferuje najwyższej jakości usługi programistyczne zarówno dla rynku polskiego, jak i międzynarodowego. Jesteśmy dumni, że należymy do grona najszybciej rozwijających się spółek technologicznych. Naszym priorytetem jest jakość oraz innowacyjność dostarczanych rozwiązań, a nasza kultura organizacyjna opiera się na zaufaniu, współpracy i ciągłym doskonaleniu.

Chcesz rozwijać swoją karierę w obszarze sztucznej inteligencji, machine learning i MLOps? Do naszego Talent Pool poszukujemy inżynierów ML na różnym poziomie doświadczenia (junior, mid, senior), którzy będą mogli dołączyć do innowacyjnych projektów naszych klientów z branż takich jak farmacja, biotechnologia, finanse czy nowoczesne technologie.

Dlaczego Talent Pool?

Dołączając do Talent Pool RITS:

  • zyskujesz pierwszeństwo w dopasowaniu do nowych projektów,
  • możesz liczyć na indywidualne wsparcie rekruterów i opiekuna technicznego,
  • otrzymujesz dostęp do ofert dopasowanych do Twojego profilu i ścieżki kariery.
  • doświadczenie w obszarze uczenia maszynowego, AI lub data science (minimum 2 lata – w zależności od poziomu),
  • biegłość w Pythonie i bibliotekach ML (np. scikit-learn, TensorFlow, PyTorch, Keras, OpenCV),
  • znajomość zasad tworzenia oprogramowania i narzędzi typu Git, CI/CD, Docker, Kubernetes,
  • doświadczenie w pracy z danymi i SQL oraz chmurowymi rozwiązaniami (AWS/GCP/Azure),
  • dobra znajomość języka angielskiego (B2+).

Mile widziane:

  • praktyka z obszarów NLP, Computer Vision, systemów rekomendacyjnych lub forecastingu,
  • znajomość narzędzi MLOps (MLflow, Kubeflow, SageMaker),
  • doświadczenie w projektach komercyjnych w środowisku Agile.
  • przygotowanie i analizę dużych zbiorów danych,
  • tworzenie, trenowanie i wdrażanie modeli ML/AI,
  • rozwój i optymalizację pipeline’ów ML w środowiskach chmurowych (AWS, Azure, GCP),
  • współpracę z zespołami Data Science, DevOps i biznesowymi przy projektach end-to-end,
  • automatyzację procesów wdrażania i monitorowania modeli (MLOps).
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What happens when you press

One press. We do the rest.

  1. A CV for this posting

    Written against RITS's own wording, from every piece of relevant proof in your profile.

  2. 25 readers review it

    Recruiter, hiring manager, skeptic and more read every draft, round after round. You get the best round.

    The review screen in CV Rocket: how each CV was read, round by round.

  3. We apply on RITS's form

    Our application engine gets through the hardest forms there are. Where a question needs you, AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

    An application in CV Rocket: every answer filled in on the employer's form.

  4. Every reply, sorted

    RITS's answer lands in your private mailbox, and we classify it on arrival: interview, question, rejection.

    The CV Rocket inbox: each employer reply classified as an interview, an action or a rejection.

  5. Reply with AI

    AI helps you write the email, checks it and sends it. We show you whether the recruiter read it.

  6. The interview in your calendar

    Full integration with your calendar. The invitation goes straight in.

    An interview invitation in the CV Rocket inbox, added to the candidate's calendar.
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Why it works

3×

more interviews than doing it yourself with ChatGPT.

ChatGPT writes a CV and never learns what happened to it. We see every reply. For each CV we know:

  • How it was written, and how the review scored it
  • When we applied, and how long after the posting went up
  • Which posting, which company, which city
  • Who got the interview, and who heard nothing

That is how we know which CVs get called.

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The numbers game

More applications. More interviews.

Every application goes out with its own CV, written for that posting and paid once. Send enough of them and the law of large numbers finds you the job.

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What if my background isn't good enough?

We make the most of the background you have. The CV uses every piece of relevant proof your profile holds, and one of the 25 readers reads your whole profile and flags what the CV left out.

Do you really apply for me?

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