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Parallel Partners
Parallel Partners
1 – 10 Angajați
B2BFintech
Parallel Partners recrutează specialiști în tehnologia informației pentru posturi cu angajare directă în serviciile financiare și tranzacționare. Căutările sale se adresează fondurilor speculative internaționale, firmelor de tranzacționare pe cont propriu, băncilor de investiții, brokerilor online și furnizorilor de software de tranzacționare, cu expertiză deosebită în sisteme de tranzacționare de înaltă frecvență, tranzacționare algoritmică, inginerie financiară și managementul riscului. Firma de recrutare a fost fondată în 1995, are sediul în Chicago și a devenit parte a Next Step Systems în 2014.
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Locurile de muncă ale companiei

Applied Machine Learning Engineer

Build production machine learning systems for classification, retrieval, ranking, and personalization. Develop reliable models, evaluation pipelines, and deployment infrastructure.

MLMali
120.000 $ – 160.000 $ / an
RemoteNormă întreagăNivel mediuSeniorLimbă Obligatorie: englezăInginer de învățare automată
PythonPyTorch

Descriere

  • Build and refine machine learning models for classification, ranking, retrieval, and personalization.
  • Create efficient classifiers and improve model accuracy, precision, latency, and cost.
  • Enhance search relevance and context retrieval with embeddings, hybrid search, and reranking.
  • Develop privacy-conscious personalization models that learn from user behavior.
  • Create evaluation pipelines, labeled datasets, and metrics to assess model quality.
  • Fine-tune and adapt existing models when sufficient data is available.
  • Build and maintain machine learning training, inference, and deployment pipelines.
  • Troubleshoot production issues, monitor model performance, and deliver improvements based on real-world feedback.
  • Work with engineering and product teams to deliver reliable ML-powered features.

Cerințe

  • Experience in machine learning is required.
  • Experience in artificial intelligence is required.
  • Strong grounding in machine learning and modern neural architectures.
  • Practical experience building and deploying machine learning models in production.
  • Experience with classification, ranking, retrieval, recommendation systems, or personalization.
  • Knowledge of model evaluation, experimentation, and performance metrics.
  • Ability to write production-quality code and work with real-world datasets.
  • Ability to balance model quality, latency, cost, and reliability.
  • Strong ownership and problem-solving skills.
  • Experience with embeddings, vector search, and ranking models.
  • Experience with production machine learning systems and inference pipelines.
  • Proficiency in Python and PyTorch or JAX.
  • Willingness to complete a 60-minute coding assessment.

Beneficii

  • Medical insurance
  • Dental insurance
  • Vision insurance
  • Savings plan options
  • Paid time off

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