Entrust

1 month ago

Applied Scientist Lead - Computer Vision

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 10 hours agoStatus: Live

Job Summary

Lead a team of 6 applied scientists in London to design, train, and evaluate vision-language models for data extraction, with mobile-friendly small-footprint deployments. Collaborate with product and engineering to drive roadmap, translate research into product opportunities, and publish results. Balance hands-on coding with strategic leadership to deliver high-performance ML systems under adversarial conditions at scale.

Location: London

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Manager level

Key Responsibilities

•Define the team’s roadmap together with product and engineering leads.
•Stay up-to-date on the vision-language modelling and efficient ML literature, and translate these insights into product opportunities.
•Manage a team of 6 Applied Scientists.
•Contribute to the regular development lifecycle by contributing to dataset creation, model training and evaluation code.
•Publish research results in national and international conferences and scientific journals.

Key Requirements

•2+ years of experience leading a team of ML scientists or research engineers.
•5+ years of industry experience as an individual contributor in a machine learning science team (ML scientist or research engineer).
•Strong experience in machine learning and computer vision.
•Strong track record delivering high-performance ML-driven products.
•Strong coding skills in Python and PyTorch.

Experience:2+ yearsMachine learningComputer visionAI

Skills:LeadershipTeam managementCommunicationProblem-solving

Languages:English

Tech Stack:PythonPyTorchAWSRayPyTorch LightningWeights & Biases

Company Brief

Entrust

Provides identity, authentication, and secure transaction solutions including public key infrastructure (PKI), digital certificates, encryption, and secure issuance for payments, mobile, and enterprise environments to protect digital identities and critical communications.

Industry: Cybersecurity

Company Size: Enterprise (1,001+ employees)

Growth: Established Company

Funding: Private Equity Backed

Headquarters: Minneapolis, United States

Founded: 1994

Website LinkedIn

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Entrust

1 month ago

Applied Scientist Lead - Computer Vision

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 10 hours agoStatus: Live

Job Summary

Location: London

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Manager level

Key Responsibilities

•Define the team’s roadmap together with product and engineering leads.
•Stay up-to-date on the vision-language modelling and efficient ML literature, and translate these insights into product opportunities.
•Manage a team of 6 Applied Scientists.
•Contribute to the regular development lifecycle by contributing to dataset creation, model training and evaluation code.
•Publish research results in national and international conferences and scientific journals.

Key Requirements

•2+ years of experience leading a team of ML scientists or research engineers.
•5+ years of industry experience as an individual contributor in a machine learning science team (ML scientist or research engineer).
•Strong experience in machine learning and computer vision.
•Strong track record delivering high-performance ML-driven products.
•Strong coding skills in Python and PyTorch.

Experience:2+ yearsMachine learningComputer visionAI

Skills:LeadershipTeam managementCommunicationProblem-solving

Languages:English

Tech Stack:PythonPyTorchAWSRayPyTorch LightningWeights & Biases

Company Brief

Entrust

Industry: Cybersecurity

Company Size: Enterprise (1,001+ employees)

Growth: Established Company

Funding: Private Equity Backed

Headquarters: Minneapolis, United States

Founded: 1994

Website LinkedIn