Verified Job
Jobs
FULL STACK DATA SCIENCE ARCHITECT
Jobs
#391921
Full Time
Job Description
Building Products and other Intellectual Property that can be used across solutions for multiple clients
Develop new ideas and apply AI/ML to specific product challenges across Enterprise Operations
Study and innovate in artificial intelligence/machine learning and its application in diverse domains
Design competitive AI/ML services and user experience for next generation devices and create prototypes for demonstration
Development of end to end AI based product.
Deep understanding of computer architecture with knowledge of Computer Vision
Proven and demonstrated implementation skills (putting theory into practice).
Must have 4 years of expert-level understanding of Artificial Intelligence technologies including some or all of knowledge representation & reasoning (KRR), natural language processing (NLP), speech recognition, computer vision, unsupervised machine learning, and/or reinforcement learning
Leverage the power of new patterns and architectures (Serverless Microservices, Event Sourcing, etc) and technologies (Kafka, Elixir, TensorFlow, Node.js, Docker, Go) to build cloud-native style solutions for the enterprises and industry verticals.
Experience leading an agile team.
Experience designing and leading engineering systems and DevOps, i.e., managing the process of building software.
Experience with more than one programming language (Java, Kotlin, Scala, Clojure, JavaScript, Go, Elixir, Erlang, Python, or Rust preferred)
Hands on experience with Amazon Web Services, Google Cloud Platform, or Azure; namely choosing platform components and assembling application and runtime architecture
Experience with the Serverless framework and serverless architecture.
Experience with microservices architectures and constituent technologies (hapijs, gokit, Spring Cloud)
Experience with containerization and container platforms. (e.g. Docker, Kubernetes, Docker EE, OpenShift, Mesosphere)
Experience with Event Driven Architectures and constituent technologies (e.g. Kafka, Kinesis) and patterns (Event Sourcing, CQRS, etc.)
Functional programming experience (e.g., in Kotlin, Scala, Clojure, Erlang, Elixir)
Experience with high performance networking (Quic, network layer optimization) or realtime transaction protocols/methods (HTTP2, Server Sent Events, MQTT, WebSockets)
Experience with distributed NoSQL databases (Cassandra, Riak, ScyllaDB, Aerospike, etc
Develop new ideas and apply AI/ML to specific product challenges across Enterprise Operations
Study and innovate in artificial intelligence/machine learning and its application in diverse domains
Design competitive AI/ML services and user experience for next generation devices and create prototypes for demonstration
Development of end to end AI based product.
Deep understanding of computer architecture with knowledge of Computer Vision
Proven and demonstrated implementation skills (putting theory into practice).
Must have 4 years of expert-level understanding of Artificial Intelligence technologies including some or all of knowledge representation & reasoning (KRR), natural language processing (NLP), speech recognition, computer vision, unsupervised machine learning, and/or reinforcement learning
Leverage the power of new patterns and architectures (Serverless Microservices, Event Sourcing, etc) and technologies (Kafka, Elixir, TensorFlow, Node.js, Docker, Go) to build cloud-native style solutions for the enterprises and industry verticals.
Experience leading an agile team.
Experience designing and leading engineering systems and DevOps, i.e., managing the process of building software.
Experience with more than one programming language (Java, Kotlin, Scala, Clojure, JavaScript, Go, Elixir, Erlang, Python, or Rust preferred)
Hands on experience with Amazon Web Services, Google Cloud Platform, or Azure; namely choosing platform components and assembling application and runtime architecture
Experience with the Serverless framework and serverless architecture.
Experience with microservices architectures and constituent technologies (hapijs, gokit, Spring Cloud)
Experience with containerization and container platforms. (e.g. Docker, Kubernetes, Docker EE, OpenShift, Mesosphere)
Experience with Event Driven Architectures and constituent technologies (e.g. Kafka, Kinesis) and patterns (Event Sourcing, CQRS, etc.)
Functional programming experience (e.g., in Kotlin, Scala, Clojure, Erlang, Elixir)
Experience with high performance networking (Quic, network layer optimization) or realtime transaction protocols/methods (HTTP2, Server Sent Events, MQTT, WebSockets)
Experience with distributed NoSQL databases (Cassandra, Riak, ScyllaDB, Aerospike, etc
