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Machine Learning Infrastructure Strategist

1 week ago

India Sigmaways Inc Full time
Job Description

Sigmaways Inc is seeking a Senior Machine Learning Engineer to lead the design, implementation, and optimization of our end-to-end ML infrastructure. As a key member of our team, you will provide technical leadership, guide a team of ML engineers, and drive best practices for model development, deployment, and scaling.

Key Responsibilities:
  • Lead the implementation of cutting-edge ML infrastructure, encompassing all facets from model inception to deployment.
  • Provide exceptional technical leadership, mentoring, and guidance to a team of machine learning engineers.
  • Take ownership of critical projects and initiatives, providing project leadership and ensuring successful delivery.
  • Collaborate closely with data scientists to translate intricate model requirements into optimized data pipelines.
  • Spearhead the establishment of best practices for model versioning, experiment tracking, and model evaluation.
  • Architect and execute model deployment strategies, harnessing containerization and orchestration for exceptional scalability and reliability.
  • Engineer automated CI/CD pipelines that facilitate seamless model deployment, monitoring, and continuous optimization.

Qualifications:

We are looking for a seasoned professional with extensive experience orchestrating the development of end-to-end machine learning infrastructure. The ideal candidate should have a proven record of transformative leadership, guiding technical teams to achieve remarkable outcomes and innovation.

  • Extensive experience in orchestrating the development of end-to-end machine learning infrastructure.
  • Proven record of transformative leadership and technical guidance.
  • Proven track record of delivering sophisticated ML solutions with high quality.
  • Exceptional problem-solving and analytical skills.
  • Solid understanding of data structures, algorithms, and software design principles.
  • Proficient in machine learning frameworks such as TensorFlow or PyTorch.
  • Deep expertise in containerization and orchestration.
  • Thorough comprehension of software engineering principles and collaborative development workflows.
  • Adeptness with cloud platforms and utilization of cloud-native services.
  • Track record of successfully integrating DevOps practices and CI/CD pipelines.