We’re working with one of our favorite long term clients in the streaming media space, offering exciting technical challenges at scale in a well run and positive growth-minded engineering environment.
We’re seeking to add a Machine Learning Engineer (working remotely), to help build, train, and maintain models that help us predict network anomalies and image degradation before they occur. You will be building, training and productionalizing models to analyze video stream quality, and then make recommendations to the infrastructure engineering teams. You will also help continue to build solid ML ops, as well as advance methodology, technology, and mindset.
In this role, you will:
Productionalize and deploy machine learning models, in close collaboration with Data Scientists
Create ML frameworks for use across the organization, with an eye towards scalability, performance and extensibility
Act as a Lead and SME for Machine Learning Engineering: You’ll evangelize new solutions, approaches, and technologies, and stay at the forefront of ML Engineering
Leverage statistical methodologies to ensure accuracy and efficiency
Buildout machine learning models, backend services, and ML frameworks
5+ years of professional software development experience.
3+ years of programming experience with Python including functional programming.
3+ years of experience in cloud platforms such as AWS.
3+ years of experience in ML pipelines using Kubeflow and AWS Kinesis.
2+ years of experience in TensorFlow and Keras.
2+ years of experience in statistical analysis using tools like Jupyter Notebooks.
2+ years of experience in ML libraries such as Scikit Learn and Statstools.
2+ years of experience in data exploration frameworks such as AWS Glue and Pandas.
3+ years of experience in data visualization tools such as Seaborn and Matplotlib.
Team player and able to communicate with other team members.
3+ years of experience in Machine Learning and Data Science modelling using Jupyter notebooks.
2+ years of experience in working with component and end-end data science metrics.
2+ years of experience in Linear algebra and optimization methods such as convex optimization.
2+ years of experience in AI/ML models particularly in NLP, Generative and Discriminative learning.
3+ years of experience in the machine learning models including but not limited to Random Forests, GBT, MART, LambdaMART, Generative Additive Models, Deep Neural Networks.
2+ years of experience in feature extraction and engineering using tools like FFMPEG to extract features from video streams.
2+ years of experience with machine learning in the broadcast industry
This is a fully remote consulting opportunity, based in the Puget Sound. Unfortunately at this time, we are not able to provide sponsorship for employment and request no agency submissions. Thank you!
We’re Rooster Park (http://www.roosterpark.com/), and we’re passionate about matching your dreams with our partners' needs. We're an equal opportunity employer who celebrates diversity, and chooses to work with similarly open-minded clients. We pay competitively and have excellent healthcare and other benefits.