Senior or Staff ML Platform Engineer

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Requirements:

• Write high-quality code. We mostly work in Python.
• Experience across the entire spectrum of data engineering, including: Data stores (e.g., ClickHouse, ElasticSearch, Postgres, Redis, and Neo4j), Data pipeline and workflow orchestration tools (e.g., Airflow, DBT, Luigi, Azkaban, Storm), Data processing technologies and streaming workflows (e.g., Spark, Kafka, Flink), Deployment and monitoring infrastructure in public cloud platforms (e.g., Docker, Terraform, Kubernetes, Datadog)
• Loading, querying and transforming large data sets
• AI and ML Integration tools like MLflow, Feast, ONNX, Apache Beam
• You're comfortable working with noisy, dirty, and unstructured data to cleanse, scrape and convert it into structured data

Responsibilities:

• Build and enhance AI/ML Model Performance
• Ensure data accuracy, consistency, and reliability, leading to better model training and inferencing
• Build low latency high throughput pipelines to enable real-time AI applications
• Enable AI-powered insights for quick decision-making
• Integrate and evaluate new AI technologies, accelerating innovation
• Help optimize operational costs while adding value
• Collaborate with data science, engineering, and business teams to shift focus on model building instead of data wrangling by embedding AI models into applications and platforms