Job Title

Applied Machine Learning Engineer - Media Search and Recommendation Location New York Business Area Engineering and CTO Ref # 10049313 Description & Requirements Our Team Bloomberg Media empowers global business leaders with breaking news, expert opinion and proprietary data distributed with global reach. With millions of unique visitors each month, our flagship website is the go-to destination for those looking to stay ahead of the curve. As one of the top 10 most visited financial and news sites on the web, we take pride in delivering top-quality content that our audience can trust. The Search and Personalization team owns the core discovery experiences on and the Bloomberg mobile app. We are responsible for how users search for, discover, and engage with content across a global audience, with a strong focus on personalization and recommendations. By powering Bloombergu2019s discovery hub, we play a critical role in helping users find the content that matters most to them, ensuring experiences are relevant, timely, and high quality. Our systems operate at web scale and sit at the intersection of backend services, data pipelines, and user-facing experiences. We are looking for a dedicated and experienced Machine Learning engineer to join the team. The ideal candidate will have a passion for Machine Learning, building distributed web scale systems and partnering with a variety of stakeholders within our expansive organization. What's in it for you As a senior engineer on the Search and Personalization team, you will play a key role in expanding Bloomberg Mediau2019s investment in personalization. Youu2019ll work closely with product managers, data scientists, and machine learning engineers to design and build systems that power personalized discovery experiences for millions of users. Youu2019ll have ownership over impactful projects, from shaping technical direction to delivering production systems. The role offers a mix of backend, data, and potentially some frontend work, giving you the opportunity to influence the personalization models that deliver results to users. Youu2019ll be working on systems that are central to Bloomberg Mediau2019s growth and directly visible to a global audience. Weu2019ll trust you to u00b7 Lead the design and delivery of personalization and recommendation systems that power discovery across and mobile platforms. u00b7 Build and maintain data pipelines that support personalization, experimentation, and model-driven product experiences. u00b7 Design, develop, and evolve backend services and APIs that deliver personalized content at scale with low latency. u00b7 Partner closely with the data science team to productionize models and enable rapid experimentation. u00b7 Collaborate across the stack, including with frontend engineers, to deliver cohesive and high-quality user experiences. u00b7 Make architectural decisions, drive technical discussions, and help set technical direction for the personalization platform. u00b7 Mentor other engineers and raise the overall technical bar of the team. You need to have u00b7 5+ years of industry experience in an Object Oriented Programming language, preferably Python or Java u00b7 5+ years of industry experience working with large data sets, performing machine learning model experimentation, implementation and deployment. u00b7 A Bacheloru2019s degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent professional experience. Weu2019d love to see u00b7 Exposure building and developing a content recommendation system, focusing on recommendation algorithms and machine learning capabilities u00b7 Familiarity building user behavioral models to predict users likelihood to perform high value actions like propensity to subscribe or churn u00b7 Experience with end-to-end machine learning projects, including data analysis, feature engineering, model selection, hyper-parameter tuning, model deployment and ongoing performance monitoring. u00b7 Hands-on expertise with big data systems and distributed data processing technologies such as Spark u00b7 Proven track record building and maintaining data pipelines that power customer-facing product features. u00b7 Demonstrated leadership delivering machine learning projects from inception through delivery. u00b7 Practical expertise with public cloud platforms such as AWS. u00b7 Proven ability to operate and evolve web-scale distributed systems in production. Salary Range = 165000 - 260000 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. Discover what makes Bloomberg unique - watch our for an inside look at our culture, values, and the people behind our success.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