Pomiń do treści
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Senior Machine Learning Engineer (LLMs)

deepsense.ai

Oferta w skrócie
22 00030 000PLN / mies.
🏠ZdalnieTryb pracy
📄B2BKontrakt
⏱️Senior · 5+ latDoświadczenie
LokalizacjaKraków
Aktywna
Opublikowano25 sierpnia 2026
Ostatnio sprawdzono25 sierpnia 2026
Wygasa za30 dni
Werdykt JobHunt

Senior ML Engineer focused on building and deploying LLM-based solutions into production. You'll work on RAG, agentic frameworks, fine-tuning, inference optimization, and collaborate across teams. Projects are client-facing and go beyond PoCs.

Brakuje: recruitment process (number of stages, timeline), information about on-call duties.

🛠 Wymagane (Must Have)
Dane źródłowe
Mile widziane (Nice to Have)
Dane źródłowe
GCPNoSQLUser Interface
AI Insights
Czym naprawdę jest ta rola?ML Engineer

Senior ML Engineer focused on building and deploying LLM-based solutions into production. You'll work on RAG, agentic frameworks, fine-tuning, inference optimization, and collaborate across teams. Projects are client-facing and go beyond PoCs.

Plusy
  • Partnerships with top AI companies (OpenAI, NVIDIA, Anyscale, etc.)
  • Active contribution to popular open-source project (ragbits)
  • Clear career path with technical or leadership tracks
  • Access to PhD-level researchers and domain experts
Na co uważać
  • !No information about team structure or on-call expectations
  • !Broad technology stack may be overwhelming
  • !Client projects may vary in domain and complexity
Codzienna praca
  • Building and optimizing ML/LLM pipelines using LangChain, LlamaIndex, or similar frameworks
  • Fine-tuning and quantizing LLMs using techniques like LoRA and prompting
  • Designing and implementing APIs for production-grade model serving
  • Collaborating with Data Scientists and Software Engineers to integrate models into applications
  • Monitoring and maintaining deployed models (MLOps: CI/CD, logging, observability)
  • Contributing to open-source projects like ragbits
  • Exploring and adapting new AI technologies (e.g., agentic frameworks, inference optimization)
  • Working with vector databases (Pinecone, FAISS, Weaviate) for RAG systems
Więcej o ofercie
Dla kogo jest ta oferta
Profil idealny

Oferta dla doświadczonych specjalistów (Senior).

Minimum sensowne

ML Engineer with at least 4 years of experience, including production LLM work, Python proficiency, basic cloud (Azure) and MLOps knowledge, and willingness to quickly learn advanced frameworks.

Raczej nie dla

Juniors or mid-level engineers with less than 4 years of ML experience, or those without production experience with LLMs/GenAI.

Ocena dopasowania
Junior1/5
Mid2/5
Senior5/5
Hands-on5/5
Architekt2/5
Remote5/5
Enterprise3/5
Pytania do rekrutera
  • ?How many team members are you working with in ML/LLM projects?
  • ?Are there on-call duties for production models? If so, frequency?
  • ?Will I work on a single client project at a time or multiple concurrently?
  • ?What is the typical project duration?
  • ?How is performance evaluated and career progression defined?
  • ?Is the remote work fully remote or are there occasional in-person meetings?
Brakujące informacje
  • Recruitment process (number of stages, timeline)
  • Information about on-call duties
  • Whether working on one or multiple projects simultaneously
  • Detailed client collaboration model
Zespół

Collaborative and innovative team with strong emphasis on knowledge sharing and cutting-edge AI research; opportunity to contribute to open-source projects.

Wynagrodzenie vs rynekn=17 · Senior · AI/ML · B2B

Na poziomie rynkowym

Ta oferta22 000–30 000 zł

≈ 131,0–178,6 zł/h

Mediana: Senior · AI/ML · Python · B2B22 00028 560

Dane z aktywnych ofert zawierających technologię Python. Pełne statystyki zarobków →

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