Senior AI/ML Engineer (AdTech-Fintech domain experience is a must)
Experience: 8+ years
Work mode: Hybrid
Key Responsibilities
Machine Learning Delivery: Design, implement, and ship scalable ML solutions for core AdTech use cases (targeting, ranking, pacing, measurement). Own features end-to-end from experimentation to production rollout.
- ML System Design: Build and evolve the ML lifecycle data preparation, training, evaluation, and real-time inference, ensuring models integrate cleanly with ad-serving systems and meet low-latency, high-throughput requirements.
- Technical Contribution: Contribute to the AI/ML technical roadmap by evaluating tools and techniques (including deep learning, LLMs, and retrieval/feature systems). Make pragmatic trade-offs with an eye toward maintainability and operational excellence.
- AI & Agentic Applications: Develop and integrate LLM-powered features and agentic workflows that assist with campaign workflows such as audience insights, bid/budget recommendations, and creative generation within well-defined guardrails.
Required Qualifications:
5+ years of experience in software engineering and/or applied machine learning, with a track record of shipping ML systems to production.
- Experience designing and building high-throughput, low-latency services or data pipelines for large-scale applications.
- Working knowledge of the programmatic advertising ecosystem (DSP/SSP/RTB) is a plus; strong adjacent experience (recommendation, ranking, marketplaces) is also valued.
- Proficiency in at least one of Java, Go, or Python for backend services and ML tooling.
- Hands-on experience with ML frameworks (PyTorch or TensorFlow) and common modeling approaches (classification, ranking, embeddings, deep learning).
- Experience with big data and streaming frameworks (e.g., Spark, Kafka) for processing and analyzing large datasets.
- Experience deploying ML to cloud environments (preferably AWS) and operating services at scale.
- Familiarity with data stores (SQL/NoSQL) such as PostgreSQL/MySQL, Cassandra/DynamoDB, Redis, etc.
- Familiarity with containerization/orchestration (Docker, Kubernetes) and CI/CD practices.
- Strong communication skills and ability to collaborate across disciplines; comfortable explaining technical
- concepts to both technical and non-technical stakeholders.
- Experience with Large Language Models (LLMs) and generative AI applied to advertising (e.g., ad copy
- generation, creative optimization, or personalized messaging).
- Experience designing and implementing agentic workflows that support autonomous or semi-autonomous
- decision-making with strong safety/observability guardrails.
- Experience with model serving and optimization for real-time inference (latency-critical environments).
- Familiarity with modern data lake and table formats (e.g., Apache Iceberg, Apache Hudi) for managing large-scale analytical datasets.
- Knowledge of microservices architecture and event-driven design patterns in distributed systems.
- Contributions to open-source projects, publications, or speaking engagements that demonstrate thought
- Leadership in AI/ML is a plus.
