Key Responsibilities:Operationalize leading data and analytics technologies while following best practices.
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 contribute 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.

Data Scientist

Job Description

Required Skills