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Egnyte

Compare

4.1

based on 22 Reviews

Video summary

7 Egnyte Jobs

Principal Machine Learning Engineer

Egnyte

4.1

based on 22 Reviews

6-10 years

Kolkata, Mumbai, New Delhi + 4 more

1 vacancy

Principal Machine Learning Engineer

Egnyte

posted 1 day ago

Job Role Insights

Flexible timing

Key skills for the job

Python Machine Learning Cloud Publishing Deep Learning Monitoring

+ 4 more

Job Description

Description

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 17,000 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 doers, thinkers, and collaborators are 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 22,000 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 .

ABOUT THE ROLE

Egnyte is seeking a Principal Machine Learning Engineer to drive innovation and leadership across machine learning initiatives, with a special emphasis on NLP solutions. As a Principal Engineer, you will play a pivotal role in shaping the future of AI/ML at Egnyte by defining technical strategy, overseeing complex machine learning architectures, and ensuring seamless integration of ML solutions into our platform at scale. You will mentor and guide engineering teams while providing expertise in state-of-the-art ML practices, ensuring a robust production pipeline and the professional management of ML models.

WHAT YOU LL DO:

Leading the technical strategy and execution for machine learning projects across the organization.
Driving innovation in NLP and other ML solutions, ensuring alignment with Egnyte s business goals.
Architecting and overseeing scalable, production-ready machine learning systems.
Providing technical leadership and mentorship to the ML engineering team, fostering growth and collaboration.
Conducting in-depth research and staying abreast of advancements in machine learning and deep learning technologies.
Collaborating with cross-functional teams, including Product, to evaluate business requirements and determine optimal ML solutions.
Designing, deploying, and managing the lifecycle of machine learning models, including retraining and monitoring for continuous improvement.
Reviewing code, offering best practices, and ensuring the delivery of high-quality solutions.
Representing Egnyte s technical excellence through publications, presentations, and participation in industry events.

YOUR QUALIFICATIONS:

Proven expertise in leading machine learning initiatives, particularly in NLP.
Extensive experience in creating and deploying machine learning & deep learning models at scale in a SaaS or Cloud environment.
Demonstrated ability to define and execute technical strategy for ML projects.
Advanced knowledge of ML frameworks, such as PyTorch and TensorFlow/ Keras .
Proficiency in tools like HuggingFace libraries (transformers and tokenizers) or Fairseq .
Expertise in Python, Docker, Kubernetes, and Helm.
Excellent communication skills, particularly in mentoring, knowledge sharing, and cross-team collaboration.
Strong experience in managing large-scale datasets and distributed computing environments, with a preference for Google Cloud Platform expertise

What we offer:

Opportunity to work on cutting-edge machine learning projects at scale.
Leadership role in a growing, innovative AI/ML team.
Support for continued learning, certifications, and professional growth

Bonus points:

Proficiency in additional programming languages such as Java, Scala, or Go.
Familiarity with tools and frameworks like Kubeflow and OpenCV.
Deep understanding of advanced analytical modeling and statistical forecasting techniques.
Demonstrated expertise with transformer-based architectures (e.g., BERT, GPT).
Experience publishing and presenting complex technical work to a broader audience.