- Company Name
- Kaluza
- Job Title
- Machine Learning Engineer
- Job Description
-
**Job title**
Machine Learning Engineer
**Role Summary**
Design, implement, and production‑scale machine learning and generative AI (GenAI) solutions to support product teams. Requires end‑to‑end ML lifecycle experience, strong Python expertise, and MLOps practices. Collaboration and clear communication with cross‑functional stakeholders are essential.
**Expectations**
- Deliver data‑driven recommendations and forecasting models that directly impact product outcomes.
- Own the complete ML pipeline: data preprocessing, model training, evaluation, deployment, and monitoring.
- Operate effectively in an agile, ambiguous environment, balancing multiple priorities.
- Communicate technical results to both technical staff and senior leadership.
- Foster an open, collaborative ML/AI community across the organization.
**Key Responsibilities**
- **ML & GenAI Development**: Create algorithms using Python (Scikit‑learn, Pandas, NumPy) and GenAI APIs.
- **Productionization**: Deploy models via microservices, manage containerization (Docker), and integrate with AWS, Databricks, Kafka ecosystems.
- **Ops & Monitoring**: Implement MLOps pipelines (MLflow, SageMaker, CI/CD), monitor performance, set alerts, and maintain version control (Git).
- **Collaboration**: Work with product managers, engineers, and analysts to identify high‑impact problems; translate business questions into model solutions.
- **Knowledge Sharing**: Mentor other data scientists, contribute to internal documentation, and promote best practices for data science, ML, and AI.
**Required Skills**
- Strong Python programming and familiarity with core ML libraries.
- Experience deploying GenAI solutions in production.
- Hands‑on with MLOps tools (MLflow, SageMaker, Docker, CI/CD).
- Knowledge of data streaming (Kafka), cloud platforms (AWS), and data processing (Databricks).
- Solid foundation in statistics, hypothesis testing, and probability.
- Excellent communication and stakeholder engagement.
- Agile work experience.
*Optional*: Experience with Scala.
**Required Education & Certifications**
- Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or related field.
- Professional certifications in machine learning, data engineering, or cloud services are a plus.