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Egnyte

Senior Machine Learning Engineer

Posted 12 Days Ago
Be an Early Applicant
Remote or Hybrid
Hiring Remotely in India
Senior level
Remote or Hybrid
Hiring Remotely in India
Senior level
The role involves fine-tuning and training SLMs, optimizing models for inference, deploying them to edge devices, and building MLOps pipelines, while monitoring performance in production.
The summary above was generated by AI

EGNYTE YOUR CAREER. SPARK YOUR PASSION.

Egnyte is a place where we spark opportunities for amazing people. We believe that every role has meaning, and every Egnyter should be respected. With 23,000 customers worldwide and growing, you can make an impact by protecting their valuable data. When joining Egnyte, you’re not just landing a new career, you become part of a team of Egnyters who are doers, thinkers, and collaborators who embrace and live by our values:

Invested Relationships

Fiscal Prudence

Candid Conversations

 

ABOUT EGNYTE

Egnyte is the secure multi-cloud platform for content security and governance that enables organizations to better protect and collaborate on their most valuable content. Established in 2008, Egnyte has democratized cloud content security for more than 23,000 organizations, helping customers improve data security, maintain compliance, prevent and detect ransomware threats, and boost employee productivity on any app, any cloud, anywhere. For more information, visit www.egnyte.com.

 

WHAT YOU’LL DO: 

  • Fine-tune and train SLMs using Hugging Face, TRL, and adapter methods (LoRA, QLoRA, PEFT)
  • Optimize models for inference via quantization, pruning, and knowledge distillation
  • Deploy models to edge devices, mobile, and local servers with strict latency targets
  • Build end-to-end MLOps pipelines from data ingestion to deployment
  • Monitor model accuracy, latency, and hardware utilization in production
  • Evaluate model quality using benchmarking frameworks and custom evaluation suites

YOUR QUALIFICATIONS:

  • SLM Development & Fine-tuning: Train and fine-tune SLMs using Hugging Face and Knowledge on Adaptors.
  • Model Optimization: Apply quantization, pruning, knowledge distillation, and optimization for lightweight, efficient models.
  • Edge Deployment: Deploy models to edge devices, mobile, and local servers, etc.
  • Pipeline Engineering: Build end-to-end MLOps pipelines — from data ingestion to deployment.
  • Performance Monitoring: Track model accuracy, latency, and CPU/GPU usage in production.

GOOD TO HAVE

  • Deployment experience on edge or mobile environments
  • Knowledge of ONNX export and cross-platform inference
  • MLOps tooling — experiment tracking, model registries, CI/CD for ML

BENEFITS

  • Competitive salaries
  • Medical insurance and healthcare benefits for you and your family
  • Fully paid premiums for life insurance
  • Flexible hours and PTO
  • Gym reimbursement
  • Childcare reimbursement
  • Group term life insurance

EQUAL EMPLOYMENT OPPORTUNITY

At Egnyte, we celebrate our unique differences and thrive on our diversity for our employees, our products, our customers, our investors, and our communities. Our global Egnyte Employee Communities (EECs) support representation and inclusion across our diverse workplace. Egnyters are encouraged to bring their whole selves to work and to appreciate the many differences that collectively make Egnyte a higher-performing company and a great place to be.

Any employees with questions or concerns about equal employment opportunities in the workplace are encouraged to bring these issues to the attention of [email protected]. Egnyte will not allow any form of retaliation against employees who raise issues of equal employment opportunity. If employees feel they have been subjected to any such retaliation, they should contact [email protected]. To ensure the workplace is free of artificial barriers, violation of this policy including any improper retaliatory conduct will lead to discipline, up to and including discharge. All employees must cooperate with all investigations conducted pursuant to this policy.

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