8+ years of experience in software, data, or ML engineering, including 5+ years in MLOps or operationalizing AI / ML workflows. Deep hands-on experience with Python, Spark / PySpark, SQL, and orchestration tools such as AirflowProven experience with public cloud platforms, preferably GCP (Vertex AI, GKE, Cloud Run) or AWS. Skilled in Databricks, FastAPI, and containerized environments using Docker, KubernetesDeep understanding of CI / CD pipelines, version control systems (e.g., Git), and infrastructure-as-code (Terraform)Expertise with MLOps tools like MLflow, Kubeflow, or similar for model tracking, versioning, deployment, and monitoring. Proficient with model monitoring frameworks (e.g., Prometheus, Grafana) and implementing model drift, performance degradation, and rollback mechanismsDemonstrated ability to contribute to roadmap execution, and deliver outcomes. Self-motivated, proactive, and comfortable working both independently and collaboratively across engineering, data science, and business teams. Strong communication and stakeholder engagement skills, with a focus on impact and executionYour Benefits
- GLOBAL DIVERSITY Diversity means many things to us, different brands, cultures, nationalities, genders, generations even variety in our roles. You make us unique!
- ENTERPRISING SPIRIT- Every role adds value. Were committed to helping you develop and grow to realize your potential.
- POSITIVE IMPACT Make it personal and help us feed the world.
- INNOVATIVE TECHNOLOGIES - You can combine your love for technology with manufacturing excellence and work alongside teams of people worldwide who share your enthusiasm.
- MAKE THE MOST OF YOU Benefits include health care and wellness plans and flexible and virtual work option .
Skills Required
Python, Spark, Pyspark, Sql, Databricks, FastAPI