The Bloomberg Connectivity & Integration group is changing the way our Enterprise clients connect and integrate with Bloomberg by building an Integration Platform-as-a-Service (iPaaS) offering, giving clients a flexible generic tool to self-service their needs. We engineer technology for high throughput and low-latency secure data transfer over a distributed cloud-based infrastructure.

Our team, CIS Analytics, provide a highly scalable, high throughput architecture for processing hundreds of millions of events a day, in order to provide observability to our iPaaS offering. We achieve observability by providing monitoring and alerting solutions using big data technologies such as Flink, Kafka and Hbase.

We are expanding our offering to include Predictive Analytics such as:

1. General anomaly detection over the traffic that flows through our data delivery platform and alert our customers using our streaming platform
2. Federated data exploratory framework to detect unusual patterns offline.
3. User recommendations - recommend the alerts which users should subscribe to, so they don't miss important failures.

What’s in it for you:

The Machine Learning Software Engineer will be a member of a growing team with responsibilities for designing and developing highly scalable machine learning solutions that impact many areas of our business. The individual in this role will help in the design and development of ML solutions based on our reference architecture which is underpinned by big data (incl. streaming) technology, micro-service architecture and high performing compute infrastructure.

Typical daily activities include contributing to all phases of algorithm development including ideation, prototyping, design, and development production implementation.

You need to have:

• Bachelors/Masters in Computer Science
• Strong background in software engineering and data science with expertise in machine learning algorithms, statistical analysis tools, and distributed systems
• 3-4 years of industry experience of working in a distributed compute environment and building ML solutions that have been deployed to production

We’d love to see:

• Broad knowledge of machine learning APIs, tools, and open source libraries
• Strong coding skills and fundamentals in data structures, predictive modeling and big data concepts
• Experience working with Java, Python, Scala, Sci-kit, SparkML
• Excellent communication skills with multiple levels of the organization
• Has experience working with streaming technologies like Apache Flink