ML Ops Architect Lead

1 month ago


Bengaluru, Karnataka, India Tetrahed INC Full time
Strategic ML Ops Leadership

Tetrahed INC is seeking a seasoned ML Ops Architect Lead to drive the company's ML Ops strategy and roadmap. As a key member of our team, you will oversee the design, development, and implementation of ML Ops platforms, frameworks, and processes.

Key Responsibilities
  • Strategic Leadership: Define and drive the overall ML Ops strategy and roadmap, aligning it with business objectives and technical capabilities.
  • Technical Architecture: Design and implement scalable, reliable, and efficient ML Ops architectures, selecting and integrating appropriate tools, technologies, and frameworks to support the ML lifecycle.
  • Team Management: Lead and mentor a team of ML Ops engineers and architects, fostering collaboration and knowledge sharing among team members.
  • Innovation and Research: Stay up-to-date with emerging ML Ops trends and technologies, researching and evaluating new tools and techniques to enhance ML Ops capabilities.
Requirements
  • 11+ years of experience in ML Ops, with a proven track record of designing and implementing large-scale ML pipelines and infrastructure.
  • Strong experience in distributed computing frameworks (Spark, Hadoop), graph databases, and auto ML libraries.
  • Bachelor's or Master's degree in computer science, analytics, mathematics, or statistics.
  • Proficiency in Python, SQL, and containerization technologies (Docker, Kubernetes).
  • Experience with CI/CD pipelines, model monitoring, and MLOps platforms (Kubeflow, MLFlow).
  • Proficiency in cloud platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes).
Preferred Skills
  • Certifications in cloud platforms or ML technologies.
  • Strong problem-solving and analytical skills.
  • Ability to plan, execute, and take ownership of tasks.
Keywords

ML Ops Architect, Azure DevOps, Docker, Kubernetes, TensorFlow, MLFlow, Pipeline, Machine Learning Platform Engineer, Data Science Platform Engineer, DevOps Engineer (with ML focus), AI Engineer, Data Engineer, Cloud Engineer (with ML focus), Software Engineer (with ML focus), Model Deployment Specialist, MLOps Architect, CI/CD, PyTorch, Scikit-learn, Cloud Computing, Big Data, Azure, Google Cloud Platform, Vertex AI, AWS, Amazon SageMaker


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