Related skills
java nosql python tensorflow sparkπ Description
- ML infrastructure: feature engineering, training, versioning, deployment, serving, evaluation, monitoring.
- Data analysis and feature engineering for multiple use cases.
- Model training for batch and real-time predictions using various algorithms.
- Production ops: debugging, performance measurement, optimization on large clusters.
- Collaborate with product managers, data scientists, and engineers to deliver impactful solutions.
- Stay current with emerging ML technologies and industry trends.
π― Requirements
- Bachelors, Masters, or PhD in CS, Statistics, or related field.
- 6+ years in industry; PhD valued.
- Strong coding skills; Spark, Python, Java.
- Real-time evaluation of models with low latency.
- Distributed ML frameworks such as Spark-MLlib and TensorFlow.
- Spark, Hive; NoSQL (Aerospike/ScyllaDB) experience.
π Benefits
- Hybrid work: in-office Mon-Thu; Fridays remote.
- Mental health and financial wellness resources.
- Healthcare, life, disability, dental, and vision coverage.
- Commuter benefits and retirement options.
- Generous time off and personal leave policies.
- Accommodations available on request.
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