Machine Learning Engineer

Key Responsibilities

• Architect and Develop AI/ML Pipelines:

  • Design and implement large-scale, production-grade AI/ML pipelines using appropriate tools and algorithms.
  • Lead the full end-to-end ML lifecycle: model development, deployment, monitoring, and optimization for both on-prem and cloud environments.

• Data Solution Design and Management:

  • Define, develop, and sustain data solutions including storage, processing units, and user interfaces for industrial-grade applications.
  • Build multi-tenant data collectors and storage systems.
  • Implement streaming and batch data processing for near-real-time flows.

• Data Modeling and Quality:

  • Design scalable data models (SQL and NoSQL).
  • Assess and improve data quality across incoming data flows.
  • Apply data management and security best practices.

• Analytics and Visualization:

  • Develop customizable analytical dashboards for stakeholders.
  • Ensure strong testing and quality assurance practices throughout development.

• Innovation and Technology Evaluation:

  • Stay updated on emerging technologies and evaluate opportunities for integration.
  • Contribute to continuous improvement of AI/ML solutions and processes.

Qualifications

• Education: Master’s or Ph.D. in Computer Science, Data Engineering, Machine Learning, or related field.

• Experience:

  • Proven experience in designing and deploying AI/ML solutions at scale.
  • Strong background in data engineering and pipeline development.
  • Hands-on experience with cloud platforms (AWS, Azure, GCP) and on-prem solutions.

• Technical Skills:

  • Proficiency in Python, SQL, and NoSQL databases.
  • Experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn).
  • Knowledge of data streaming tools (Kafka, Spark) and containerization (Docker, Kubernetes).
  • Experience working with Microsoft solutions and Databricks is a plus
  • Familiarity with CI/CD and MLOps practices.

• Soft Skills:

  • Strong problem-solving and analytical mindset.
  • Ability to work collaboratively in cross-functional teams.
  • Excellent communication and documentation skills.