DevJobs

Senior Machine Learning Engineer

Overview
Skills
  • Python Python ꞏ 4y
  • ML ML ꞏ 4y
  • TensorFlow TensorFlow
  • Spark Spark
  • ML ML
  • Kafka Kafka
  • NoSQL NoSQL
  • AWS AWS
  • GCP GCP
  • Azure Azure
  • Docker Swarm Docker Swarm
  • Kubernetes Kubernetes
  • SQL databases
  • MLRun
  • Tecton
  • Streaming technologies
  • Spark Structured Streaming
  • Serving platforms
  • Seldon Core
  • Sagemaker
  • BentoML
  • Public cloud provider
  • ECS
  • MLFlow
  • Big data systems
  • Containers orchestration
  • Kubeflow
  • KServe
  • Feature Stores
  • Feast
  • etc.
  • etc

What is the job?

ironSource (recently merged with Unity) Aura, a revolutionary large scale mobile platform, is looking for an outstanding and passionate machine learning engineer to join our team.

Join our team and you'll have an opportunity to research, design, implement, and evaluate a variety of advanced ML algorithms using the latest technology.


Responsibilities:

  • Designing machine learning systems and self-running artificial intelligence (AI) software to automate predictive models
  • Transforming data science prototypes and applying appropriate ML algorithms and tools
  • Build a full ML lifecycle models including model monitoring capabilities
  • Solving complex problems with multi-layered data sets, as well as optimizing existing machine learning libraries and frameworks


Requirements:

  • Bachelor's degree in computer science, engineering or a related field.
  • 4+ years experience as a machine learning engineer
  • 4+ years of experience with Python or other relevant languages.
  • Extensive knowledge of ML frameworks and ML libraries
  • Experience with training, testing, deployment, and monitoring real-time (or near real-time) ML models in production
  • Experience running ML systems in production, with knowledge on how to generate predictions for ML frameworks with high throughput and low latency
  • Deep understanding of data structures, data modeling, and software architecture (including microservices, SOLID principles, and event driven architecture)
  • Experience in SQL databases and NoSQL solutions


Advantage:

  • Experience in Spark and big data systems
  • Experience in high volume production systems (billions of events per day)
  • Experience with leading ML platforms (Kubeflow, MLFlow, Sagemaker, Tensorflow)
  • Experience with leading serving platforms (Seldon Core, KServe, BentoML, Tensorflow, SageMaker, MLRun)
  • Hands on experience with Feature Stores (Feast, SageMaker, Tecton, etc)
  • Experience in streaming technologies (Kafka, Spark Structured Streaming, etc.)
  • Experience with containers orchestration (K8S, Docker Swarm, ECS)
  • Experience in major public cloud provider (AWS, GCP, Azure)
Unity