Description

You will build and deploy production-grade machine learning models to solve complex business challenges.

Responsibilities

• Execute the full ML lifecycle, including data preparation, feature engineering, model training, evaluation, and deployment.
• Assemble modular components into end-to-end systems to ensure seamless integration.
• Collaborate with Data Scientists to facilitate experimentation, model construction, and validation.
• Use Jupyter Notebooks for prototyping and collaborative experimentation.
• Contribute to the continuous improvement of machine learning systems by implementing advancements in software engineering.

Required Skills

• 5+ years of experience with a BS or MS in Computer Science or equivalent.
• 3+ years of experience in framework-based model development, optimization, or efficient deep learning techniques.
• Proficiency in Python, R, or Scala.
• Expertise in TensorFlow and PyTorch.
• Experience with Kubernetes, Spark, Airflow, and Kafka.
• Experience working with petabyte-scale datasets in Databricks, Snowflake, or similar platforms.
• Knowledge of open-source LLMs and machine learning ecosystems.
• Proficiency with CI/CD solutions for MLOps and LLMOps, including automation with IaC such as Terraform.
• Hands-on experience with Scikit-learn, Pandas, NLTK, and spaCy.

Key Skills

Education

BS or MS in Computer Science