Bloomberg Law is changing the legal industry by delivering the most sophisticated legal tech platform on the market with a focus on automation, analytics, and real-time answers! Our goal is to become an indispensable tool for legal professionals by supporting their day-to-day tasks and providing solutions that help them get real-time answers and better serve their clients.
The MLOps engineer will be part of the Platform Engineering group within BLAW that develops and supports cloud native solutions and tools to deploy and operate BLAW products at scale on public cloud (AWS) environments. The team focuses on implementing platform-as-a-service (PaaS) frameworks, tools and workflows to accelerate product development. As a MLOps engineer at Bloomberg Law, your mission is to design and build reliable and scalable cloud solutions to run diverse workloads on AWS. Our culture of diversity, intellectual curiosity, methodical problem solving and openness in a blameless environment are keys to our success. A good fit for our team is a person who is self-motivated, proactive, a good collaborator and comfortable with ambiguity.
Legal AI is an exciting and rapidly evolving field. If you are interested in working with a highly collaborative team to develop innovative solutions and make a big impact, please apply!
We'll trust you to:
Work closely with ML Engineers and application engineers responsible for deploying ML models to have a good understanding of their MLOps needs to speed up ML Development.
Collaborating with internal AI platform teams to understand availability of internal tools as well as tools available in AWS
Leverage open source tools and building frameworks and components to improve and scale our Serving and ML platform.
Be a partner to Application teams and ML Engineers in designing cost and compute-optimal workflows for their use cases.
Build and maintain infrastructure as code (IaC) in the cloud, that can scale when needed.
Provide documentation and templates to make the onboarding the new workflows easy and seamless.
You'll need to have:
4+ years of experience programming in OOP (Java/Python)
Proficiency with AWS (EC2, S3, SageMaker)
A degree in Computer Science, Engineering or related technology field/Equivalent Experience
We'd love to see:
Working knowledge of ML Development Lifecycle, experience in developing MLOps solutions and working with machine learning teams
Familiarity of common ML frameworks such as PyTorch, Tensorflow, and Scikit-learn
Prior experience with container technologies like Docker, Kubernetes, Buildpacks, etc.
Experience with optimizing model performance on CPUs, GPUS (embedded hardware optimization is a plus)
Curiosity to solve new problems and keep learning new technologies.
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 maternity/parental leave, protected veteran status, status as a victim of domestic violence, or any other classification protected by applicable law.
Bloomberg provides reasonable adjustment/accommodation to qualified individuals with disabilities. Please tell us if you require a reasonable adjustment/accommodation to apply for a job or to perform your job. Examples of reasonable adjustment/accommodation include but are not limited to making a change to the application process or work procedures, providing documents in an alternate format, using a sign language interpreter, or using specialized equipment. If you would prefer to discuss this confidentially, please email AMER_recruit@bloomberg.net (Americas), EMEA_recruit@bloomberg.net (Europe, the Middle East and Africa), or APAC_recruit@bloomberg.net (Asia-Pacific), based on the region you are submitting an application for.
Salary Range: 160,000 - 240,000 USD Annually + Benefits + Bonus The referenced salary range is based on the Company's good faith belief at the time of posting. Actual compensation may vary based on factors such as geographic location, work experience, market conditions, education/training and skill level. We offer one of the most comprehensive and generous benefits plans available and offer a range of total rewards that may include merit increases, incentive compensation [Exempt roles only], paid holidays, paid time off, medical, dental, vision, short and long term disability benefits, 401(k) +match, life insurance, and various wellness programs, among others. The Company does not provide benefits directly to contingent workers/contractors and interns.