Arrow Electronics
Arrow Electronics
Arrow Electronics is a global technology solutions and supply chain company serving technology manufacturers and service providers. Its work spans value-added distribution, supply chain management, marketing and business development support, emerging technology solutions, design engineering, data center management, and IT asset disposition. Through this broad portfolio, Arrow supports the development, delivery, and lifecycle management of technology products across industries, helping make advanced technologies more accessible and easier to bring to market.

AI/ML Engineer

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

Description

  • 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.

Requirements

  • 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.

Benefits

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

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