Senior Machine Learning Solutions Architect

2 weeks ago

Bengaluru, Karnataka, India beBeeData Full time ₹ 1,04,000 - ₹ 1,30,878

Job Overview:

We are seeking a highly skilled Senior Machine Learning Software Engineer to drive the development of cutting-edge AI/ML solutions. As a key member of our team, you will play a pivotal role in designing, building, and optimizing machine learning infrastructure while collaborating with product managers, data scientists, and engineers to bring innovative models into production.

Key Responsibilities:

  • Partner with product managers to understand customer requirements, design prototypes, and deploy solutions to production.

Design, build, harden, and maintain the core infrastructure supporting the ML platform and lifecycle.

  • Define and contribute to the technology strategy, roadmap, and priorities for AI/ML initiatives.
  • Automate every aspect of the ML infrastructure to minimize human intervention and improve efficiency.
  • Encourage and implement best practices in data engineering and software development.
  • Write high-quality, production-grade code that aligns with company standards and contributes to new standardization efforts.
  • Implement automated testing to ensure reliability and correctness of ML models and infrastructure.
  • Review and mentor other engineers to promote high-quality engineering practices.
  • Actively participate in technical communities-of-practice and continuing education programs to advance personal and organizational growth.
  • Facilitate problem diagnosis and resolution across technical and functional areas.

Required Skills & Competencies:

  • 8+ years of experience in software engineering, machine learning, or data engineering.
  • Expertise in designing, coding, and scripting to develop real-world AI/ML solutions.
  • Strong programming skills in Python, Java, or Scala with hands-on experience in ML frameworks.
  • Experience with ML model deployment, MLOps, and automation.
  • Proficiency in cloud-based ML solutions.
  • Knowledge of data pipeline orchestration tools.
  • Strong background in data engineering concepts.
  • Experience working with containerization.
  • Strong analytical and problem-solving skills with a collaborative mindset.
  • Excellent communication and leadership skills with the ability to mentor and guide junior engineers.

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