Senior Machine Learning Engineer at Integral Ad Science

Paris, Île-de-France, France

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Advertising, TechnologyIndustries

Requirements

Advanced degree (MSc, PhD or equivalent industrial experience) in a relevant technical field (machine learning, computer science, computer vision, etc)
5+ years of industry experience delivering machine learning systems from ideation to production
Strong programming skills in Python and experience with deep learning frameworks (e.g., Pytorch, Tensorflow)
Good experience developing deep neural networks (CNN, transformers), preferably applied to NLP, computer vision, or audio processing
Experience with source control workflows and deploying ML models in production (experience with inference frameworks such as Tensorrt, Onnx, or Triton is a plus)
Comfortable manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources
A continuous learner with a strong interest translating theory into practical solutions
Experience distilling product requirements into problem definitions, dealing with ambiguity and competing objectives
Ability to communicate complex quantitative analysis in a clear, precise, and actionable manner
What puts you over the top
Practical experience with image/video classification, object detection, speech recognition, machine translation, and similar problems
Publication record in deep learning / neural networks or adjacent fields
Experience working with distributed computing tools applied to machine learning (Ray, horovod), or to data processing and cloud platforms (AWS, GCP)

Responsibilities

Scope work and projects in the realm of machine learning, focusing on deep learning applications in image/video classification
Work with a variety of data sources to build production-ready ML models
Apply machine learning to novel problems in online advertising
Collaborate with engineers to integrate solutions within larger engineering workflows
Effectively communicate results from ML/DL models and statistical learnings to a variety of stakeholders within R&D and product organizations

Skills

Key technologies and capabilities for this role

PythonPyTorchTensorFlowDeep LearningCNNTransformersComputer VisionImage ClassificationVideo ClassificationMachine Learning

Questions & Answers

Common questions about this position

What experience level is required for this Senior Machine Learning Engineer role?

Candidates need 5+ years of industry experience delivering machine learning systems from ideation to production, along with an advanced degree (MSc, PhD or equivalent) in a relevant technical field like machine learning or computer science.

What programming skills and frameworks are required?

Strong programming skills in Python and experience with deep learning frameworks such as Pytorch or Tensorflow are required, along with good experience developing deep neural networks like CNNs and transformers.

What is the company culture like for this team?

The team maintains an open and collaborative environment where members bring diverse backgrounds and unique thinking styles, focusing on challenging technical problems in machine learning for multimodal content classification.

What salary or compensation is offered for this position?

This information is not specified in the job description.

What makes a candidate stand out for this role?

Candidates stand out with a track record of delivering deep learning models at scale, experience working cross-functionally under tight timelines, practical expertise in image/video classification or similar, publications in deep learning, and experience with distributed computing or cloud platforms.

Integral Ad Science

Digital advertising verification and optimization services

About Integral Ad Science

Integral Ad Science specializes in digital advertising verification, optimization, and analytics. The company provides solutions that ensure ads are seen by real people in safe environments and effectively reach target audiences. Its products include ad fraud detection, brand safety measures, viewability measurement, and contextual targeting, all powered by advanced data analytics and machine learning. IAS differentiates itself by offering a technology platform that delivers real-time insights and analytics, helping clients maximize their return on investment in digital advertising. The company's goal is to enhance the quality and performance of digital advertising campaigns while addressing challenges like ad fraud and brand safety, ultimately providing transparency and accountability in the advertising landscape.

New York City, New YorkHeadquarters

2009Year Founded

$48.4MTotal Funding

IPOCompany Stage

Data & Analytics, ConsultingIndustries

1,001-5,000Employees

Benefits

Healthcare: Comprehensive health insurance

Flexible PTO: Take what you need, when you need it

Retirement: 401k match in the US, country-specific pension plans

Parental leave: Full maternity and paternity leave

Community: Volunteer opportunities

Celebrating team players: Peer-nominated awards

Meals and snacks: Stocked kitchens to fuel your day

Team events: Frequent happy hours, parties and outings

Risks

CFO transition may cause financial instability or strategic misalignment.

Regulatory challenges in China could hinder IAS's expansion efforts.

Sustainability partnerships might not meet expectations, affecting IAS's reputation.

Differentiation

IAS offers AI-driven ad verification for enhanced brand safety and fraud prevention.

The company provides contextual targeting solutions amid tightening privacy regulations.

IAS's Total Visibility product optimizes supply paths with transparency in media quality.

Upsides

Expansion into China taps into the world's second-largest advertising market.

Growing demand for sustainability aligns with IAS's carbon measurement partnerships.

Increased need for AI solutions boosts IAS's market relevance and client base.

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