Bloomberg runs on data. It's our business and our product. From the biggest banks to elite hedge funds, financial institutions need timely, accurate data to capture opportunities and evaluate risk in fast-moving markets. With petabytes of data available, a solution to transform and analyze the data is critical to our success. Bloombergs Data Science Platform was established to support development efforts around data-driven science, machine learning, and business analytics. The solution aims to provide scalable compute, specialized hardware and first-class support for a variety of workloads such as ML training job and inference services, Spark, and Jupyter. The solution was developed to provide a standard set of tooling for addressing the Model Development Life Cycle from experimentation and training to inference. The solution is built using containerization, container orchestration and cloud architecture and built on top of 100% open source foundations. Production Inference is a critical step on the MDLC to realize the business value for Bloomberg AI applications and the advent of large language models (LLMs) presents new opportunities for expanding NLP capabilities in our products. The inference solution is powered by open source project KServe which is a production ready inference solution for both generative and predictive AI applications. We are poised for enormous user growth this year and have an ambitious roadmap in terms of new features as well as improved user experience. Thats where you come in. As a member of the inference team, youll have the opportunity to design and implement scalable, low latency, high throughput model inference solutions in a hybrid cloud environment. We are founding members of the KServe project to standardize ML Inference within the Kubernetes ecosystem. As part of that, we regularly upstream features we develop, present at conferences and collaborate with our peers in the industry. Open source is at the heart of our team. It's not just something we do in our free time, it is how we work. <h5 dir="ltr">Well trust you to: </h5><ul> <li dir="ltr">Interact with data scientists to understand their production use cases and requirements to advise the next set of GenAI features for the inference platform. </li> <li dir="ltr">Design solutions for problems such as scalable model deployment, low latency/high throughput inference, GPU resource optimizations and autoscaling. </li> <li dir="ltr">Automate operation and improve telemetry of the inference platform in our infrastructure stack. </li> <li dir="ltr">Design solutions for multi-cloud strategy. </li> </ul><h5 dir="ltr">Youll need to be able to: </h5><ul> <li dir="ltr">Innovate and design solutions that keep in mind strict production SLA: low latency/high throughput, multi-tenancy, high availability, reliability across clusters/data centers, etc. </li> <li dir="ltr">Fix and optimize generative inference application performance. </li> <li dir="ltr">Provide developer and operational documentation. </li> <li dir="ltr">Provide performance analysis and capacity planning for clusters. </li> <li dir="ltr">String communication and collaboration skills, with the ability to work effective with multi-functional teams </li> <li dir="ltr">Have a passion for providing reliable and scalable infrastructure. </li> </ul><h5 dir="ltr">Youll need to have: </h5><ul> <li dir="ltr">4+ years programming experience in two or more languages (e.g., Python, Go, C++) </li> <li dir="ltr">A Degree in Computer Science, Engineering or similar field of study or equivalent work experience </li> <li dir="ltr">Experience designing and implementing low-latency, high-scalability inference platform. </li> <li dir="ltr">Explore emerging inference optimization techniques </li> <li dir="ltr">Experience with debugging performance issues with distributed tracing. </li> <li dir="ltr">Experience working with a distributed multi-tenancy and multi-cluster system. </li> <li dir="ltr">Experience with distributed systems eg. Kubernetes, Kafka, RabbitMQ, Zookeeper/Etcd. </li> <li dir="ltr">Strong knowledge of data structures and algorithms. </li> <li dir="ltr">Linux systems experience (Network, OS, Filesystems). </li> </ul><h5 dir="ltr">Wed love to see: </h5><ul> <li dir="ltr">Experience Large Language Model Inference, especially vLLM, TensorRT-LLM runtimes. </li> <li dir="ltr">Design, develop, test and deploy inference solutions for LLMs </li> <li dir="ltr">Experience with Kubeflow/KServe, MLFlow, Sagemaker. </li> <li dir="ltr">Experience working with GPU compute software and hardware. </li> <li dir="ltr">Ability to identify and perform OS and hardware-level optimizations. </li> <li dir="ltr">Open source involvement such as a well-curated blog, accepted contribution, or community presence. </li> <li dir="ltr">Experience with cloud LLM providers such as AWS Redrock, Gemini or Azure OpenAI. </li> <li dir="ltr">Experience with configuration management systems (Terraform, Ansible) </li> <li dir="ltr">Experience with continuous integration tools and technologies (Jenkins, Git, Chat-ops) </li> </ul><h5 dir="ltr">Learn more about our work using the links below: </h5><ul> <li dir="ltr">Keynote: Platform Building Blocks: How to build ML infrastructure with CNCF projects - https://www.youtube.com/watch?v=ncED2EMcxZ8 </li> <li dir="ltr">The State and Future of Cloud Native Model Inference - </li> <li dir="ltr">https://www.youtube.com/watch?v=786VaGAfm6I </li> <li dir="ltr">The Hitchhiker's Guide to Kubernetes Platforms: Dont Panic, Just Launch! https://www.youtube.com/watch?v=a84mwXicpdc </li> </ul>

With ever-increasing channels of communication and heightened regulatory scrutiny, organizations need to continuously archive and monitor their activities and data. Our clients seek a one-stop shop for compliant storage and reconstruction of communication, collaboration, and financial transaction information. Thats where Bloomberg Vault (BVAULT) steps in. Thousands of organizations trust BVAULT to manage and archive their enterprise communications and trade data, including Bloomberg Message, Instant Bloomberg, email, instant messages, mobile data, files, voice data, social media, and more. As a Senior Software Engineer within the BVAULT Archive Metadata team, you will be pivotal in designing and implementing systems that harness metadata to unlock the full potential of the petabytes of data we collect. Metadata plays a key role, not just in organizing data, but in understanding how it moves through systems, uncovering valuable insights, and enabling advanced analytics using AI/ML. You will work with state-of-the-art tools to ensure our datasets are optimized for analysis and reporting, empowering the business to make faster, more informed decisions. In this role, youll also be at the forefront of applying metadata to the next generation of cutting edge applications such as trade reconstruction and surveillance, where it provides essential context and structure for more accurate model training. By leveraging metadata, we solve complex business challenges, driving innovation and value at scale. As part of this dynamic and young team, youll have the opportunity to shape the future of this critical infrastructure from the ground up. Key Responsibilities: <ul> <li dir="ltr">Build scalable, distributed data ingestion and processing pipelines. </li> <li dir="ltr">Develop data models and architecture for data lakes. </li> <li dir="ltr">Optimize data retrieval for dashboards and reporting. </li> <li dir="ltr">Ensure compliance with data governance and security standards. </li> <li dir="ltr">Collaborate with stakeholders to deliver data-driven solutions. </li> <li dir="ltr">Monitor performance and recommend infrastructure improvements. </li> </ul>You'll need to have: <ul> <li dir="ltr">4+ years of experience as a Data Engineer, Software Engineer or similar role. </li> <li dir="ltr">4+ years experience with SQL, Python, Java or C++. </li> <li dir="ltr">Strong skills in distributed systems and open-source technologies. </li> <li dir="ltr">Excellent problem-solving and communication skills. </li> <li dir="ltr">A Degree in Computer Science, Engineering, Mathematics, similar field of study or equivalent work experience. </li> </ul>We'd love to see: <ul> <li dir="ltr">Experience with open-table formats (e.g., Parquet), cloud platforms (e.g., S3), and technologies like Apache Iceberg, Spark, Kubernetes and Airflow/Argo. </li> </ul>Why Join Us? Our team prioritizes maintaining a healthy work-life balance through clear communication and setting realistic project timelines. We foster a supportive environment that allows our engineers to thrive both personally and professionally. Additionally, we dedicate four weeks at the end of the year for Innovation Month, where team members are encouraged to collaborate on engineering-driven projects and explore new technologies. Interested? For more information, visit our Compliance Flickr page: Compliance Flickr Page.

Team Overview:

Our data moves global financial markets – and conversations around that data are central to how markets are shaped. Our group, Core Communications, builds the infrastructure responsible for delivering real-time communications between the 350k financial professionals on the Bloomberg Terminal. Our email (MSG) and instant message (IB) products deliver billions of messages across millions of chat rooms per day, including stock quotes, trade confirmations, breaking news alerts or help desk inquiries among others, forming one of the largest financial networks in the world and placing our team at the center of our universe! Our users rely on these products because of their real-time performance, extensive scale, ironclad security, tight integration with financial data and applications.

The CC Search Team, part of Bloomberg’s Community Group, focuses on delivering a powerful, intuitive search experience within IB (Instant Bloomberg) and MSG platforms. Given the vast volume of information shared daily across these platforms, efficient search functionality is vital. Our mission is to empower Bloomberg users with a seamless and reliable search experience, enabling them to find relevant communication content easily and efficiently. As part of the CC Search Team, you’ll have a direct impact on improving user productivity—whether it’s by streamlining access to information with a single button press or ensuring all relevant quotes, news, and research articles are at their fingertips.

Our scalable search offering is already built on top of Apache Solr and distributed across hundreds of machines, handling a million user queries every day. Currently, we’re focused on advancing the user experience by making search more intuitive, measurable, and precise. This includes developing robust methods to assess and improve search quality and leveraging vector search to enable semantic understanding of user queries. Through optimized retrieval and ranking, our goal is to deliver the most relevant results to users with minimal overhead.

Technology Stack:

Languages: Java17 (Gradle), C++, Python3.8, Typescript

Frameworks: SpringBoot, React

Technologies: Solr, Lucene, Cassandra, Kafka, Redis

Misc: Docker (Local Development)

We’ll trust you to:

Build large, scalable, real time distributed systems

Explore Solr, Lucene and other open source technologies to solve problems

Drive full stack solutions with user experience as primary focus

Collaborate with product managers, designers, engineers on your team to conceptualize and build new features to keep our product competitive and cater to the demands of our clients

Participate in code reviews and improve software engineering practices, tooling and processes across the team

You’ll need to have:

4+ years professional experience working in a Java Ecosystem

A high level of motivation, a strong drive to enhance client-facing products, and a deep technical curiosity.

Working knowledge of modern development methodologies and tools (Jenkins / Maven / Jira)

BA, BS, MS, PhD in Computer Science, Engineering or related technology field

We’d love to see:

Full stack development experience

Experience with building large scale distributed systems

Experience with building full-text search systems with Solr, Lucene, ElasticSearch

Experience with driving large projects with ambiguous requirements

A track record of open-source contributions

Interviewing with us

We believe interviewing is a two way street. It's a way for us to get to know you and your skills, and also a way for you to learn more about the team, our technical challenges, and what you'd be working on. The content of each interview round will be tailored to the role and your background.

Salary: 160000,240000,USD,Annual

Bloomberg is an equal opportunity employer and we value diversity at our company. We do not discriminate on the basis of age, ancestry, color, gender identity or expression, genetic predisposition or carrier status, marital status, national or ethnic origin, race, religion or belief, sex, sexual orientation, sexual and other reproductive health decisions, parental or caring status, physical or mental disability, pregnancy or parental leave, protected veteran status, status as a victim of domestic violence, or any other classification protected by applicable law.

Bloomberg is a disability inclusive employer. Please let us know if you require any reasonable adjustments to be made for the recruitment process. If you would prefer to discuss this confidentially, please email amer_recruit@bloomberg.net

Software Engineer Bloomberg Lp Jobs

Senior Software Engineer Ai Platform Engineer
December 31, 2024

Senior Software Engineer Archive Metadata
December 31, 2024

Senior Software Engineer Core Communications Search
December 28, 2024

Quick filters

Top companies

Software Engineer Bloomberg Lp Jobs

Senior Software Engineer Ai Platform EngineerDecember 31, 2024

Senior Software Engineer Archive MetadataDecember 31, 2024

Senior Software Engineer Core Communications SearchDecember 28, 2024

Quick filters

Top companies

Senior Software Engineer Ai Platform Engineer
December 31, 2024

Senior Software Engineer Archive Metadata
December 31, 2024

Senior Software Engineer Core Communications Search
December 28, 2024