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Machine Learning

Lisboa

Descrição da posição

Client is looking for a Software Engineer to integrate the Artificial Intelligence Platform team. Your primary focus will be to contribute to the ongoing development of ML-powered services. You will also help to develop end-to-end machine learning pipelines, from data collection strategies to inference services deployments, building AI/ML frameworks and solutions at scale. The ideal candidate will have some experience as a software engineer and a deep interest in building ML products.

Responsibilities

Work closely with Data Scientists to bring ML-powered services into production.
Build robust and scalable Web-based APIs to serve our ML models.
Help building frameworks that reuse technical solutions to known problems, while also promoting solution sharing among projects/departments.
Evangelize the adoption of frameworks that accelerate the solution of machine learning problems at scale.
Be part of the creation of machine learning pipelines, referencing strategies from data collection to inference services building and deployment.
Collaborate with DevOps, software architecture, and platform teams.
Regularly contribute to the documentation of our systems and tools.

Skills Valued:

Fluency in one at least one OOP language such as C# or Java.
Experience with common data science languages, such as Python or R. Excellence in at least one of these is highly desirable.
Familiarity with machine learning libraries such as TensorFlow or Scikit-Learn.
Clear understanding of the machine learning project lifecycle.
Familiarity with streaming/messaging platforms such as Kafka or RabbitMQ.
Experience with at least one data processing tool such as Spark, Beam, Flink, etc.
Experience with at least one cloud platform such as Azure, AWS, GCP, etc.
Proficiency in using query languages such as SQL, Spark SQL, etc.
Experience with at least one NoSQL database, such as MongoDB, Redis, Cassandra, etc.
Experience with container technologies like Docker and Kubernetes.
Experience with software build and release processes, unit testing, version control, etc.
Experience using Git source control
Very good scripting skills and understanding of the Linux/Unix command line.
A passion for ML/AI.
A collaborative and can-do attitude.
Excellent written and verbal communication skills, comfortable with audiences including product and engineering management.

Requirements

Fluency in C# and Python.
Experience automating infrastructure to train, evaluate, and deploy ML algorithms.
Experience with Azure and many of its products (Databricks, CosmosDB, AKS, Azure DevOps).
Experience with at least one NoSQL database, such as MongoDB, Redis, Cassandra, etc.
Experience with at least one data processing tool such as Spark, Beam, Flink, etc.
Experience with streaming platforms, Kafka is a plus.
Experience with microservices architectures.
Experience developing Web-based APIs in different flavors (REST, RPC, gRPC).
A GitHub/GitLab profile with projects demonstrating some of the candidate’s skills.

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