Senior AI ML Engineer

2-3 per week you need to be available until 9:00 pm due to meetings with the US team.

Altimetrik Poland is a digital enablement company. We deliver bite-size outcomes to enterprises and startups from all industries in an agile way to help them scale and accelerate their businesses. We are unique in Poland's IT market. Our differentiators are an innovation-first approach, a strong focus on core development, and an ability to attack the challenging and complex problems of the biggest companies in the world.

In this role, you’ll help us build the Payments Machine Learning Platform that accelerates the pace of ML development and the deployment of impactful, high quality ML use cases within Payments. This is a platform-focused role (ML infrastructure and pipelines), not primarily new model/algorithm development. 

Responsibilities:

• Build and continuously improve ML systems and pipelines supporting Payments (training, batch/stream processing, and serving).

• Hands-on develop, productionize, and operate ML training and inference pipelines at scale, including both batch and (where applicable) real-time use cases.

• Leverage third-party and in-house tools & infrastructure to develop reusable platform components that enable fast iteration, reliable deployments, efficient serving, and easier long-term upkeep of ML systems.

• Example projects include: workflow standardization, distributed training reliability, offline/online consistency, reproducibility, and platform/tooling migrations.

And if you possess...

• 5+ years of experience building production ML systems (MS/PhD a plus)

• Strong coding skills in Python

• Deep understanding of production ML best practices (training/serving skew, offline/online parity, reproducibility, data quality, monitoring/observability) and solid understanding of core ML modelling and evaluation (experimentation/A/B testing, common algorithms including deep learning and optimization) to effectively debug and improve ML systems in production.

• Experience with 3 or more of these technologies: TensorFlow/PyTorch, Kubernetes, Spark, Airflow (or equivalent), Kafka (or equivalent), data warehouse (eg. Hive), distributed computing/training frameworks (eg. Ray)

• Industry experience building and operating end-to-end ML infrastructure and pipelines (training and inference) is a strong plus.

🔥We grow fast.

🤓We learn a lot.

🤹We prefer to do things instead of just talking about them.

If you would like to work in an environment that values trust and empowerment... don't hesitate, just apply!