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Arrow Electronics
Arrow Electronics
Sponsor pentru viza H1BConsultanțăIndustria prelucrătoareLogistică
Arrow Electronics este o companie globală de soluții tehnologice și lanțuri de aprovizionare, care deservește producători de tehnologie și furnizori de servicii. Activitatea sa acoperă distribuția cu valoare adăugată, gestionarea lanțurilor de aprovizionare, sprijinul pentru marketing și dezvoltarea afacerilor, soluții pentru tehnologii emergente, inginerie de proiectare, gestionarea centrelor de date și casarea activelor IT. Prin acest portofoliu extins, Arrow sprijină dezvoltarea, livrarea și gestionarea ciclului de viață al produselor tehnologice în diverse industrii, contribuind la accesibilizarea tehnologiilor avansate și la introducerea lor mai ușoară pe piață.
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AI/ML Engineer

Build scalable MLOps pipelines and LLM solutions for eInfochips’ engineering services. Develop, monitor, and govern machine learning systems.

INIndiaLa sediuNormă întreagăNivel mediuSeniorLimbă Obligatorie: englezăInginer de învățare automată
AWSAzureGoogle Cloud PlatformHadoopKafkaKerasNoSQLNumpyPandasPythonPyTorchScikit-LearnSparkSQLTensorFlow

Descriere

  • Develop AI and machine learning solutions.
  • Architect scalable MLOps pipelines with Azure ML, MLflow, Databricks Asset Bundles (DAB), and CI/CD/CT.
  • Implement supervised, unsupervised, and reinforcement learning models.
  • Engineer features and assess model performance.
  • Track model drift and set up automated alerts.
  • Establish data governance, lineage tracking, metadata management, and compliance processes.
  • Design and deploy LLM solutions using RAG, Agentic AI, MCP, and prompt engineering.
  • Create Power BI dashboards for model monitoring and business KPI reporting.
  • Use sound software engineering practices in machine learning code.
  • Evaluate practical uses for Generative AI, Agentic AI, and LLMs.
  • Mentor junior colleagues, review code, and lead technical knowledge-sharing sessions.

Cerințe

  • 4–8 years of experience.
  • A notice period of 0–45 days is preferred.
  • Strong knowledge of supervised, unsupervised, and reinforcement learning, model evaluation, and feature engineering.
  • Proficiency in TensorFlow, PyTorch, and Keras.
  • Hands-on experience with CNNs and RNNs.
  • Advanced Python skills, including NumPy, Pandas, and scikit-learn.
  • Practical experience with Spark; Databricks experience is preferred.
  • Familiarity with Hadoop and Kafka.
  • Experience with machine learning services, data storage, and compute on Azure, AWS, or GCP.
  • Strong MLOps experience.
  • Strong SQL, NoSQL, and data modeling skills.
  • Hands-on experience detecting and monitoring model drift and setting up automated alerts.
  • Practical experience implementing data governance frameworks, lineage tracking, metadata management, and compliance.
  • Experience architecting scalable MLOps pipelines with Azure ML, MLflow, Databricks Asset Bundles (DAB), and CI/CD/CT.
  • Microsoft Certified: Azure Data Scientist Associate certification is a plus.
  • Experience designing and deploying LLM solutions using RAG, Agentic AI, MCP, and prompt engineering is a plus.
  • Experience building Power BI dashboards for model monitoring and business KPI reporting is a plus.
  • A strong foundation in statistics, hypothesis testing, and data interpretation is a plus.
  • Knowledge of software engineering practices for reusable, testable, and maintainable machine learning code.
  • Knowledge of Generative AI, Agentic AI, and LLMs.
  • Ability to mentor junior colleagues, review code, and lead technical knowledge-sharing sessions.

Beneficii

  • Competitive pay
  • Work-life balance
  • Professional development
  • Innovative work environment
  • Recognition and rewards

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