O

AI Engineer

OpsMx
3.6 / 5
Malappuram Not disclosed
21 hours ago
On-Site
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About the job

Job Description • Architect and build a scalable AI platform, defining the infrastructure required to support large-scale ML, simulations, and deep learning workloads. • Establish and drive best practices across the AI / ML lifecycle, including model training, evaluation, optimization, and deployment. • Lead and mentor a team of engineers, fostering a collaborative and innovation-driven environment. • Work closely with product and business stakeholders to translate high-level problems into clear implementation plans. • Own and guide technical architecture decisions and oversee team deliverables and recommendations. • Collaborate with cross-functional teams to align on project goals, timelines, and outcomes. • Stay current with AI / ML technologies, frameworks, and industry trends, and apply them where relevant. • Support customers and internal users in effectively adopting and using the AI platform. • Contribute to the growth of junior engineers through coaching and hands-on guidance. • This role is expected to evolve as the business and platform mature. The responsibilities outlined above represent current priorities and may expand based on organizational needs. Requirements : • 10+ years of experience in engineering, computer science, or a related quantitative field. • 4+ years of hands-on experience in AI / ML or closely related domains. • Strong foundation in AI / ML fundamentals with a solid software engineering background. • Proven experience leading large-scale, multi-stakeholder technical initiatives. Nice to Have : • Working knowledge of Application Security, DevOps, Kubernetes, and public cloud platforms. Candidate available to join immediately are preferred.

Requirements

  • AI
  • ML
  • Software Engineering

Preferred Technologies

  • AI
  • ML
  • Software Engineering

About the company

OpsMx focuses on building scalable AI platforms and employs a collaborative environment to innovate and support large-scale ML and deep learning workloads.

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