About the job
Location: Hybrid – New York City / Remote
Department: Engineering
Reports to: VP of Engineering
Job Type: Full-Time, Hybrid (Remote with occasional in-office collaboration)
About the Role:
We are seeking an experienced AI Systems Engineer to join our core technical team. In this role, you’ll be responsible for the design, generation, deployment, upkeep, and optimization of the data and inference systems that power our AI-driven applications. You’ll ensure our pipelines run reliably, our data remains clean and queryable, and our models stay accurate and performant in production. This role sits at the intersection of data engineering, machine learning, and infrastructure. You’ll collaborate across teams to ship features, debug systems, and push intelligent functionality into our products. If you thrive on owning critical systems end-to-end, enjoy the challenge of scaling real-time AI, building models that boost campaign performance, and know how to keep cogs down and queries fast, we’d love to hear from you.
Key Responsibilities:
AI System Architecture:
- Own the architecture that connects data pipelines, inference systems, and real-time decisioning.
- Continuously improve targeting and budget efficiency via closed-loop learning from live campaign outcomes.
- Ensure the full stack, from ingestion to activation, supports measurable, ongoing performance gains.
- Implement retraining pipelines, drift detection, and inference reliability.
Data Infrastructure & Pipeline Reliability
- Design, build, and maintain robust data pipelines (batch and real-time) that power analytics and inference systems.
- Manage data workflow orchestration and job dependencies to ensure timely, predictable delivery across the stack.
- Ensure high data quality, low-latency processing, and end-to-end reliability through proactive monitoring, alerting, and fault-tolerant design.
Data & Insights Delivery
- Combine and curate data from multiple sources to create unified, analysis-ready datasets for real-time and batch workflows.
- Design processes and tools to enable fast, flexible exploration of large datasets while balancing query speed, expressiveness, and cost efficiency.
- Build data pipelines that extract, transform, and structure information to surface actionable insights for audience analysis, campaign performance, and model monitoring.
- Collaborate with client services, analysts and the product team to identify high-value insights and deliver them in clear, accessible formats (dashboards, datasets, APIs) to drive decision-making and feature development.
Qualifications:
Experience
- 5+ years of experience in data engineering, machine learning infrastructure, or full-stack data systems roles.
- 2+ years of experience generating and working with custom models and model generation pipelines.
- Experience supporting real-time applications or analytics systems at scale, preferably in ad tech, martech, or high-throughput environments.
Technical Skills
- Languages: Proficient in Python and SQL; familiarity with Java, Scala, or Go is a plus.
- Data Infrastructure: Hands-on experience with Airflow, dbt, Kafka, Spark, or equivalent ETL/ELT and streaming tools.
- Cloud & DevOps: Strong experience with cloud environments (more than one preferred), containerization (Docker), and orchestration (Kubernetes).
- Data Warehousing: Deep familiarity with analytical databases like BigQuery, Snowflake, or Redshift.
Analytical & Problem-Solving Skills
- Strong debugging instincts, comfortable navigating logs, dashboards, and pipelines to find root causes fast.
- Ability to translate product goals into reliable data architecture and intelligent model deployment.
- Skilled at balancing system performance, cost-efficiency, and business impact.
Nice to Have
- Experience deploying, monitoring, and retraining ML/AI models in production (e.g., via SageMaker, Vertex AI, MLFlow, or similar pipelines).
- Familiarity with ad-serving systems, audience targeting, or real-time bidding dynamics.
- Understanding of data privacy frameworks (e.g., GDPR, CCPA) and their impact on data and ML pipelines.
- Experience building or operating systems that power real-time inference and decisioning at web scale.
Why Join Us?
- Work with cutting-edge technology in the fast-evolving ad tech industry.
- Hybrid work model with flexibility for remote collaboration.
- Competitive salary, equity options, and comprehensive benefits package.
- Growth opportunities within a dynamic and innovative engineering team.
- A culture of learning, mentorship, and technical excellence.
Compensation: $180,000 to $360,000
Compensation at Symitri is based on a range of factors, including job-related skills, experience, qualifications and worksite location. Final offers may vary from the listed.
Join us and help redefine the future of digital advertising!
Apply now to be part of our team.