Machine Learning Engineer

Job Description

Are you ready to revolutionize the advertising industry?

At Cognitiv, we are not just another AdTech company—we are industry trailblazers redefining media buying with our Deep Learning Advertising Platform. Since 2015, we have harnessed the power of cutting-edge deep learning technology and data science to transform how brands connect with their customers. Our mission? To bring intelligence to advertising and deliver unparalleled precision, relevance, and impact at scale.

With our innovative platform, advertisers enjoy unprecedented flexibility—whether it is activating Dynamic Deals through their preferred DSP, leveraging our managed service DSP, or utilizing our industry-first ContextGPT product. As a part of Cognitiv, you will be at the forefront of AI-driven advertising solutions, driving change and achieving remarkable growth in a rapidly evolving industry.

Now, we’re growing!

The Role

We’re seeking a Machine Learning Engineer to help build and scale the next generation of Cognitiv’s ML infrastructure. As we transition from a legacy platform to a modern, automated, and highly scalable system, you’ll play a key role in developing the tools and pipelines that power our Deep Learning Advertising Platform.

You’ll work across the full ML lifecycle — from data ingestion and model training to deployment and monitoring — helping to improve automation, reliability, and performance. This is a great opportunity for an engineer who’s comfortable writing production-quality code and eager to grow their experience in large-scale ML systems, MLOps, and distributed data workflows.

What You'll Do

Contribute to the design, development, and automation of ML workflows across data ingestion, training, deployment, and monitoring.

Build and maintain scalable data pipelines that support high-volume model training and evaluation.

Partner with senior engineers to optimize system performance and reduce operational bottlenecks.

Collaborate closely with Product, Engineering, and ML Research teams to deliver reliable, high-impact systems.

Write clean, production-level Python code and participate in code reviews to maintain quality and consistency.

Help improve monitoring and observability across ML pipelines to ensure reliability in production.

Tech Stack

Languages/Frameworks: Python (primary), PyTorch Lightning

Cloud/Infra: AWS, Docker, Apache Airflow

Data: ClickHouse, S3, distributed data processing tools

Models: Deep Learning, LLMs, Hugging Face ecosystem

Who You Are

Strong Coder. You write clean, efficient, and scalable code in Python, with an advanced degree (or equivalent experience) in Computer Science, Engineering, or a related field.

ML Systems Builder. You’ve designed or maintained ML pipelines, automation, or MLOps systems, and have a solid grasp of model training, deployment, and monitoring in production.

Distributed Data Expert. You’re experienced with distributed data processing (e.g., PySpark) and understand how to scale workflows efficiently.

Deep Learning Practitioner. You’ve worked hands-on with PyTorch (bonus for PyTorch Lightning) and bring curiosity about LLMs and the Hugging Face ecosystem.

Collaborative Engineer. You communicate clearly, thrive in cross-functional environments, and take pride in building reliable, well-architected systems.

In-Person Collaborator. You’re available to work onsite MTW in San Mateo, partnering closely with peers to accelerate progress.

Bonus Points If You Have

Exposure to LLMs or the Hugging Face ecosystem

Familiarity with AWS, Docker, and Airflow

Experience managing data at scale (e.g., S3, ClickHouse, or similar)

Knowledge of low-latency model serving

Experience in AdTech or other real-time, high-performance systems

Location & Compensation

Location: Bellevue or San Mateo (hybrid: 3 days in-office, 2 days remote)

Compensation is based on experience, skills, and other factors. Base salary is just one part of your total rewards at Cognitiv—you’ll also receive equity and a comprehensive benefits package.

Highlights include:

Medical, dental & vision coverage (some plans 100% employer-paid)

12 weeks paid parental leave

Unlimited PTO + Work-From-Anywhere August

Career development with clear advancement paths

Equity for all employees

Hybrid work model & daily team lunch

Health & wellness stipend + cell phone reimbursement

401(k) with employer match

Parking (CA & WA offices) & pre-tax commuter benefits

Employee Assistance Program

Comprehensive onboarding (Cognitiv University)…and more!