Appodeal is a dynamic US-based product company with a truly global presence.

We have offices in Warsaw, Barcelona and Virginia along with remote team members located around the world.

Our company thrives on diversity, collaboration, and innovation, making us a leader in the mobile app monetization space.

Why Appodeal?

At Appodeal, we’re more than just a company—we’re a team united by a common mission: to help every person discover and grow their talents!

We take pride in our cutting-edge product and our internationally dispersed team of talented professionals.

Here’s what we value, and what we hope you do too:

• Continuous Learning and Growth: We are passionate about learning, growing personally, and building rewarding careers.
• Making an Impact: We are committed to building a history-defining company that leaves a lasting impact on the mobile app industry.
• Solving Exciting Challenges: We tackle complex problems every day, supported by a team of world-class professionals and mentors.
• Enjoying the Journey: We believe in having fun while working toward our goals.

We are seeking an ML Engineer to take ownership of deploying and maintaining all machine-learning models in production at BidMachine. This role is pivotal in shaping how we scale our data-driven bidding strategies and enhance system performance. You will collaborate with Data Scientists, DevOps, and Backend Engineers to implement robust pipelines, optimize model performance in real-time environments, and ensure the integrity and observability of our models in production.

Responsibilities:

• Lead the transition of all current ML models (prototype, research-grade, or sandboxed) into a scalable production environment.
• Design and maintain end-to-end model deployment pipelines, from training to serving, using tools like Docker, Kubernetes, and cloud services (GCP, AWS, or similar).
  Implement model versioning, A/B testing, rollback mechanisms, and performance monitoring.
• Optimize models for latency, scalability, and throughput, especially in real-time bidding contexts.
• Collaborate with data scientists to refactor research code into clean, production-grade code.
• Ensure observability and monitoring of deployed models (e.g., Prometheus, Grafana, or similar).
• Establish and maintain ML Ops best practices, including CI/CD for ML, feature stores, and reproducibility standards.

Qualifications:

• 3+ years of experience in ML Engineering, ML Ops, or Software Engineering roles focusing on deploying machine learning models.
• Proficiency in Python and frameworks such as PyTorch, CatBoost, XGBoost, Scikit-Learn, and others.
• Experience with ONNX or other analogous technologies to deploy ML models in production environments
• Experience with containerization (Docker) and orchestration tools (Kubernetes).
  Deep understanding of cloud infrastructure (e.g., AWS SageMaker, GCP Vertex AI, etc.).
• Knowledge of real-time or low-latency systems and performance optimization.
• Strong collaboration and communication skills to partner with cross-functional teams.
  
  

Nice to haves:

• Experience with Rust for high-performance, low-latency ML serving or systems integration.
• Experience with Java/Scala for integrating ML models into backend code.
• Experience in AdTech, real-time bidding (RTB), or high-frequency decision systems.
• Familiarity with feature stores, model registries, and data versioning.
• Exposure to Kafka, Airflow, Spark, or similar distributed data processing tools.

With an outstanding product and a mission that excites and inspires, Appodeal offers a unique opportunity to make an impact while being part of an amazing team.

Join us and help shape the future of mobile app success!