MACHINE LEARNING ENGINEER

Who are you?

• 5+ years of hands-on experience building and deploying production ML solutions.
• Proficiency with Vertex AI, GCP, Hugging Face, transformers, PyTorch, scikit-learn, Airflow, GitHub, vector search, and knowledge graph technologies.
• Strong understanding of core ML concepts and deep learning methods.
• Bonus: Practical experience with recommendation systems, reinforcement learning, or learning-to-rank models.
• Strong programming skills in Python, Go, or Rust, along with solid SQL data-manipulation skills.
• Demonstrated success deploying ML models to production and managing the full end-to-end ML lifecycle.
• Excellent communication and collaboration skills for working across teams.
• (Optional) Experience working with GCP.

What will you do?

• Design, develop, deploy production-grade ML systems in the field of recommendations, personalisation and reinforcement learning. Ensure high performance, stability, observability, low latency and efficient costs, and reliability.
• Use deep expertise in algorithms, data structures, and distributed computing to architect scalable ML platforms.
• Guide the selection and implementation of ML frameworks and tooling (PyTorch, TensorFlow, Hugging Face, etc.) to ensure efficient, maintainable solutions.
• Apply strong product-development principles and champion rapid experimentation to drive continuous improvement.
• Provide direction on cloud-based ML infrastructure (Azure, GCP) to enable secure, scalable, and cost-efficient deployments.
• Drive adoption of modern data-processing and pipeline technologies (e.g., Spark, Beam, Kafka) for large-scale data ingestion and training workflows.

Desired knowledge, experience, competence, skills etc

• 5+ years of hands-on experience building and deploying production ML solutions.
• Proficiency with Vertex AI, GCP, Hugging Face, transformers, PyTorch, scikit-learn, Airflow, GitHub, vector search, and knowledge graph technologies.
• Strong understanding of core ML concepts and deep learning methods.
• Bonus: Practical experience with recommendation systems, reinforcement learning, or learning-to-rank models.
• Strong programming skills in Python, Go, or Rust, along with solid SQL data-manipulation skills.
• Demonstrated success deploying ML models to production and managing the full end-to-end ML lifecycle.
• Excellent communication and collaboration skills for working across teams.

(Optional) Experience working with GCP.

What 3 things from the box above are most important?

• 5+ years of hands-on experience building and deploying production ML solutions.
• Strong understanding of core ML concepts and deep learning methods.

Proficiency with Vertex AI, GCP, Hugging Face, transformers, PyTorch, scikit-learn, Airflow, GitHub, vector search, and knowledge graph technologies. Strong programming skills in Python, Go, or Rust, along with solid SQL data-manipulation skills.