Machine Learning Engineer (L2)
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
Salary
- $130,000-$180,000 Base Salary + Equity
What We Offer
- 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!
What You’ll Find at Cognitiv
- Festiv – We make work fun with cross-team games, events, and creative team bonding.
- Responsiv – You’ll be close to clients and leadership, influencing real outcomes.
- Inclusiv – Diversity and individuality are celebrated across all levels.
- Inventiv – We reward curiosity and embrace bold ideas.
- Transformativ – We support your growth with training, mentorship, and flexibility.
- Collaborativ – We operate across coasts, connected by purpose and teamwork.
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