Machine Learning

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.

Requirements

·        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.

The ideal candidate will have

·        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 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.