Brightcove seeks a Machine Learning Engineer to join the Brightcove Data Team and build the future of online video. As a critical member of our machine learning and artificial intelligence team, this individual will be responsible for building out machine learning pipelines to support video, audio, and text machine learning models through data transformation, feature engineering, training and deployment. Broad experience working with large volumes of unstructured data, both in batch and streaming mode, and building scalable machine learning systems with the data will be essential to being a success in this role. We are developing world-class video intelligence products powered by AI/ML for customers in the discovery and understanding of the videos, video contents, and in the automation of the processes.

This position will play a critical role in helping to define the culture of working with data to drive AI and ML inside of Brightcove. This means not only understanding the technology, but being able to justify why the adoption of that technology will be able to drive Brightcove forward.

Job Responsibilities:

• Work with a dynamic team reporting up to the Chief Data Officer to create a variety of machine learning models and systems to unlock the power of machine learning on video to Brightcove’s customers
• Analyze and extract relevant information from large amounts of videos to understand broad trends in videos across video catalogs
• Design and build cloud native scalable machine learning models and applications 
• Work with data engineers and developers to productionize the applications
• Monitor and maintain production machine learning models and applications
• Collaborate with data engineers, research scientists and product managers to push the boundaries of innovation and experimentation with best practice and cutting-edge machine learning technology

Qualifications/Experience

• 3+ years of Machine Learning Engineering experience or an advanced degree (MS or Ph.D) in Computer Science, Data Science, Machine Learning, or related field is required
• Proficiency in one or more programming languages such as Python (preferred), Scala or Java
• Knowledge and experience with relational database system and SQL
• Deep understanding of statistical modeling, machine learning, and deep learning concepts, and a track record of solving problems with these methods
• Familiarity with one or multiple industry recognized ML frameworks such as Scikit-Learn, XGBoost, PyTorch, TensorFlow, or Keras
• Experience working with major cloud providers - we make use of both AWS and GCP
• Knowledge and experience with at least one of the following three areas acquired either through academic training or industrial projects:
  • Computer Vision techniques such as image classification, object detection, object tracking, semantic segmentation, and leading computer vision libraries such as OpenCV
  • Natural Language Processing for text classification, information extraction, topic modeling, machine translation a plus
  • Content recommendation algorithms
• Excellent communication, relationship skills, and a strong team player
• Ability to adapt to ever changing, growing and transformative SaaS software technology environment; ability to shift in priorities and focus with determination and positive attitude

Preferred Qualifications/Experience

• Experience with data pipelines and large scale data stores (data lake, data warehouse, Hadoop, MapReduce, Spark)
• Experience with developing and building data-intensive solutions 
• Experience with ML Pipelines such as AWS SageMaker, GCP Vertex AI, Kube Flow Pipelines, ML Flow, or Azure ML

About Brightcove 

As the industry leader in this space, we empower our customers to deliver top-notch video experiences to audiences on every screen in bold and innovative ways. When video is done right, it can have a powerful and lasting effect. Hearts open. Minds change. Creativity thrives. Since 2004, Brightcove has been supporting customers that are some of the largest media companies, enterprises, events, and non-profit organizations in the world. There are over 600 Brightcovers globally, each of us representing our unique talents and passions and we have built a culture that values individual empowerment, excellence and collaboration. This culture enables us to develop technologies once thought impossible, provide customer support without parallel or excuses, and leverage the expertise and resources of a global infrastructure. We take our video seriously, and we take great pride in doing it as one team.

Working at Brightcove

As the undisputed global leader in powering premium video for our customers, Brightcove recruits and retains highly qualified and motivated individuals, creating an environment where people can innovate and achieve their best, and we reward them for their performance by giving them the opportunity to share in the company’s success. We offer competitive compensation, stock options, 401k matching, and tuition reimbursement, as well as generous PTO - and we expect you to use it!

We offer Remote, Hybrid, and Onsite work arrangements.  Our US based office is located in downtown Boston, in Fort Point harbor. This Brightcove office has an open working space layout with beautiful water views. Employees enjoy access to fully-stocked kitchens and social activities including: happy hours, trivia and movie nights, ping pong tournaments, and philanthropy events. We have plenty of opportunities to meet your colleagues around the globe and we also celebrate a variety of personal interests with organized groups and clubs including an Employee Action Committee, Women of Brightcove, Pride of Brightcove, Parents of Brightcove … and more!

We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, or veteran status. We are proud to be an equal opportunity workplace. If you need any accommodations for your interview, please email recruting@brightcove.com. 

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