Machine Learning Engineer at Cognitiv

San Mateo, California, United States

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Not SpecifiedCompensation

Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

AdTech, AdvertisingIndustries

Requirements

Strong coder: Write clean, maintainable, and scalable code in Python
Hands-on builder: Experience with ML pipelines, MLOps tools, or automation frameworks and thrive on improving workflows
Deep learning practitioner: Trained models with PyTorch (bonus if PyTorch Lightning) and curious about deploying large language models (LLMs)
Cloud-native thinker: Familiar with AWS services, containerization, and orchestration tools like Docker and Airflow
Collaborative engineer: Enjoy problem-solving with cross-functional partners and communicate clearly across teams
Growth-driven: Eager to take ownership, deepen technical expertise, and deliver high-impact work
In-office teammate: Available to collaborate in-person MTW in Bellevue WA or San Mateo CA

Responsibilities

Design, automate, and optimize ML workflows including data ingestion, model training, deployment, and performance monitoring
Build and maintain scalable, cloud-native pipelines that support large-scale experimentation and high-volume model training and scoring
Own core components of our MLOps stack and drive improvements around reliability, scalability, and ease of use
Partner with cross-functional teams (Product, Engineering, ML Research) to align automation efforts with business needs
Write production-grade Python code, participate in code reviews, and ensure high-quality engineering standards
Enhance our observability, logging, and alerting infrastructure to improve operational resilience and reduce time-to-detection
Propose and experiment with new tools or workflows to help modernize our ML lifecycle and platform delivery
Own the end-to-end ML lifecycle — from ingesting client data to developing, deploying, and monitoring models in production

Skills

Machine Learning

Deep Learning

MLOps

Data Pipelines

Model Training

Model Deployment

Monitoring

Cloud-Native

Distributed Systems

Data Ingestion

Automation

Scalable Systems

Real-Time Advertising

Cognitiv

AI-driven digital advertising optimization platform

About Cognitiv

Cognitiv.ai uses deep learning technology to improve digital advertising for businesses through its platform, NeuralMind™, which trains neural networks on client data. This technology enables companies to create custom algorithms for ad buying that enhance audience targeting and marketing effectiveness without requiring data scientists. Unlike its competitors, Cognitiv focuses on automating ad buying and providing actionable insights to help businesses identify new consumer segments. The company's goal is to help clients maximize their return on investment in digital advertising by leveraging their first-party data.

None, NoneHeadquarters

2015Year Founded

$3.2MTotal Funding

CONVERTIBLECompany Stage

Data & Analytics, Consumer Software, AI & Machine LearningIndustries

51-200Employees

Benefits

Health Insurance

Paid Parental Leave

Unlimited Paid Time Off

Hybrid Work Options

401(k) Retirement Plan

401(k) Company Match

Health and Wellness Stipend

Phone/Internet Stipend

Employee Assistance Program

Risks

Integration with Index Exchange may face interoperability challenges across platforms.

Exclusive partnership with Adform could encounter regulatory hurdles in Europe.

Rapid client base growth may strain operational capacity and customer support.

Differentiation

Cognitiv offers industry-specific Deep Neural Network products for Big Data decisions.

Their NeuralMind™ platform creates custom ad buying algorithms for optimized marketing.

Cognitiv's ContextGPT product enhances programmatic curation with generative AI integration.

Upsides

Partnership with Adform expands AI-driven contextual targeting in Europe.

Deep Learning Advertising Platform positions Cognitiv as a media buying pioneer.

Collaboration with Manual Labor Studio showcases visually engaging advertising solutions.

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