Senior Machine Learning Engineer

About the role

Caylent is building a talent pipeline for future senior machine learning engineering opportunities. The role involves designing and documenting ML solutions on AWS for customers, collaborating within cross‑functional delivery teams.

Key responsibilities

• Deliver machine learning solutions on AWS, including model development, MLOps, and analytics.
• Participate in daily stand‑ups, bi‑weekly agile ceremonies with customers, and weekly 1:1s with the manager.
• Process big data and prepare training datasets using Spark, Hadoop, or streaming platforms.

Required profile

• Strong experience building production ML models and using AWS ML services such as SageMaker.
• Proficiency with ML libraries (Keras, TensorFlow, PyTorch, Scikit‑learn) and MLOps tools (MLflow, Kubeflow, Airflow).
• Expertise in data processing with Python/Pandas, PySpark, Scala, SQL, and big‑data platforms.

Required skills

• Feature engineering, hyper‑parameter tuning, stochastic gradient descent, deep‑learning layer types and activation functions.
• Visualization tools like SageMaker, ggplot, matplotlib, seaborn.
• Infrastructure‑as‑code tools such as CloudFormation, Amazon CDK or Terraform.
• Excellent written and verbal communication.

What we offer

• USD‑based compensation, 100% remote work, generous holidays and flexible PTO.
• Phantom equity, paid exams and certifications, peer bonuses.
• State‑of‑the‑art laptop, equipment & office stipend, professional development plan and learning stipend.