Senior Machine Learning Engineer, WARSZAWA

Requirements:

• 4+ years of experience in machine learning, ideally in recommender systems, NLP, computer vision, or another applied ML domain.
• Degree in Computer Science, Machine Learning, Statistics, Mathematics, Operational Research, or another quantitative field.
• Strong hands-on experience building, training, evaluating, and improving ML models.
• Solid software engineering skills, including clean code, data structures, algorithms, and production readiness.
• Professional experience with Python; experience with Java, Kotlin, Go, C, or C++ is a plus.
• Experience with large-scale data pipelines, distributed processing, and orchestration tools such as Spark and Airflow.
• Familiarity with cloud-based ML environments, preferably AWS, and production serving technologies such as Kubernetes, REST, gRPC, or FastAPI.
• Strong communication skills and the ability to work cross-functionally with product, analytics, platform, data, and engineering teams.

Stack: Python, Spark, Airflow, AWS, S3, Kubernetes, recommender systems, Deep Learning, Transformers, LLMs, MLOps, REST/gRPC/FastAPI, A/B testing

We are hiring on behalf of our client, a global innovator in fitness and wellness technology. Their mission is to empower people to live fit, strong, long, and happy lives by delivering integrated experiences to millions of members anytime, anywhere.

We are looking for a Senior Machine Learning Engineer to join the Personalization team, which owns the recommendation systems powering content discovery across the ecosystem. In this role, you will work on end-to-end ML systems: building and training models, improving real-time recommendation services, running experiments, and deploying scalable solutions into production. You will help evolve the recommendation platform from multiple models toward a more unified, real-time architecture, while also contributing to company's IQ initiatives involving LLMs, personalized plans, and AI-powered member experiences.

,[Build, train, evaluate, and improve ML models powering personalized workout and content recommendations., Develop and maintain data and ML pipelines using Python, Spark, Airflow, AWS, and S3., Productionize, deploy, monitor, and optimize ML models and recommendation services., Improve real-time model serving, including latency, scalability, reliability, and infrastructure costs., Support the evolution of recommendation systems toward unified rankers, candidate generation, and inference services., Run A/B tests and analyze experiment results with Product Analysts to measure product and member impact., Contribute to IQ initiatives, including personalized plans, insights, LLM-based features, and responsible AI practices., Collaborate with ML Engineers, Data Engineers, Software Engineers, Platform Engineers, Product Managers, and Analysts to deliver scalable personalization features.] Requirements: Machine Learning, NLP, Computer vision, Clean Code, Python, Spark, Kubernetes, REST API, gRPC, Communication skills, Data pipelines, AWS, Java, Kotlin, Go, C, C++