almost 3 years ago
Buenos Aires, ArgentinaStaff+
Responsibilities
- Lead and mentor the team while fostering technical growth and best practices.
- Guide the creation of specifications and maintain clear technical documentation.
- Serve as the primary stakeholder contact to align technical and business goals.
- Develop and optimize scalable data and machine learning solutions with monitoring and MLOps practices.
- Oversee data and model lifecycles from exploratory data analysis and feature engineering through deployment and continuous improvement.
- Build proofs of concept to validate and refine solutions.
- Optimize performance, latency, memory, and throughput across data systems.
- Design and maintain feature stores and data pipelines.
- Research and implement emerging technologies.
- Participate in candidate interviews and evaluations.
Requirements
- Experience leading and mentoring teams on data projects and guiding technical decisions.
- Ability to collaborate with stakeholders, translate business needs into technical solutions, and align priorities across teams.
- Experience implementing ML-based systems, including model lifecycle management, monitoring, and MLOps pipeline setup.
- Strong proficiency in Python, Pandas, NumPy, Jupyter, Scikit-Learn, XGBoost, and Plotly.
- Knowledge of SQL.
- Experience with AWS, GCP, or Azure.
- Preferred experience with Airflow, MLflow, H2OAI, or Databricks.
- Preferred background in AdTech or Generative AI projects.
- Understanding of Keras, PyTorch, or TensorFlow.
- Solid command of English for technical communication and documentation.
- Basic knowledge of Docker.
Benefits
- Remote-first work-from-anywhere arrangement.
- AWS, dbt, Google Cloud, Azure, and Databricks certifications fully covered.
- In-company English lessons.
- Birthday off and an additional vacation week.
- Referral bonuses.
- Monthly Maslow credits for the benefits marketplace.
- Annual team trip.
- Monthly childcare reimbursement.
Tech Stack
Categories
Data EngineeringML Engineering
