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 looking for 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 more modern, automated, and highly scalable system, you’ll play a pivotal role in designing and implementing the tools, pipelines, and practices that power our deep learning and real-time advertising platform.

You’ll own the end-to-end ML lifecycle — from ingesting client data to developing, deploying, and monitoring models in production — while working closely with senior engineers, data scientists, and product stakeholders. This is a great opportunity for an engineer who’s eager to strengthen their skills in ML systems, MLOps automation, and distributed data workflows, and grow into a critical contributor on the team.

What You'll Do

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.

Tech Stack

Languages/Frameworks: Python, PyTorch, PyTorch Lightning

Cloud/Infra: AWS, Docker, Apache Airflow

Data: ClickHouse, S3, Spark, distributed data systems

Models: Deep Learning, LLMs, Hugging Face ecosystem

Who You Are:

Strong coder: You write clean, maintainable, and scalable code in Python.

Hands-on builder: You have experience with ML pipelines, MLOps tools, or automation frameworks and thrive on improving workflows.

Deep learning practitioner: You’ve trained models with PyTorch (bonus if PyTorch Lightning) and are curious about deploying large language models (LLMs).

Cloud-native thinker: You’re familiar with AWS services, containerization, and orchestration tools like Docker and Airflow.

Collaborative engineer: You enjoy problem-solving with cross-functional partners and communicate clearly across teams.

Growth-driven: You’re eager to take ownership, deepen your technical expertise, and deliver high-impact work.

In-office teammate: You’re available to collaborate in-person MTW in Bellevue WA or San Mateo CA.

Bonus Points If You Have

Experience in AdTech or real-time bidding systems

Exposure to ClickHouse, PySpark, or distributed data processing systems

Understanding of low-latency model serving architectures

Advanced degree in Computer Science, Engineering, or related field

Location & Compensation

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

Salary: $160,000-$220,000 Base Salary + Equity

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)