Multiple Locations
Responsibilities
We are looking for a Machine Learning Engineer to build world-class machine learning platform solutions. You will be responsible for empowering data scientists and AI scientists by developing a collection of industry-strength platform services to greatly improve scientists productivity and facilitate innovation. Your responsibilities include, but not limited to:
● Build Stats Perform’s Machine Learning platform and services to support major AI and Data Science use cases
● Manage the ML lifecycle, including data prep, training data generation, feature engineering, optimization, experimentation, reproducibility, deployment and end-to-end workflow management
● Enable ML and Deep Learning capabilities at vast scale by developing the necessary systems, tools, technologies and integrations as part of the ML Platform offering
● Help accelerate the velocity from idea to interference in production
● Contribute to capabilities around data programming, data augmentation (transformation function), active learning (slicing function) for training data, and transfer learning
● Engineer the de-bias, ethics, security and compliance aspects of ML pipelines, centralized feature store, model metastore, and inference metrics store etc.
● Work with partners and stakeholders to identify data acquisition opportunities, create requirements, transform large volume data into AI ready high quality relevant datasets
● Achieve quality ML data using a triad of people, process & technology
● Identify, assess and implement 3rd party technologies that may complement Stats Perform capabilities, and accelerate advancement of critical features; maintain strong collaborative relationships with 3rd party technology providers
Qualifications
● 3+ years of relevant industry experience in Data & analytics platform or machine learning and data science
● Bachelor’s degree in Engineering, Computer Science, Mathematics, Computational Statistics, Machine Learning or related STEM fields
● Verbal/written communication and presentation skills, including an ability to effectively communicate with both business and technical teams, and both internal and external stakeholders
● An open minded, structured thinker
● A team player and consensus builder
● Intellectual curiosity and excellent problem-solving skills, including the ability to structure and prioritize an approach for maximum impact
● Experience in projects involving large scale multi-dimensional datastore, complex business infrastructure, and cross-functional teams, and track-record of successfully launched ML projects in production
● Hands on experience with building enterprise grade machine learning and data platforms
● Familiarity with common machine learning algorithms (random forest, XGBoost, etc.)
● Familiarity with advanced ML techniques (neural networks/deep learning, reinforcement learning, active learning, data augmentation and GAN etc.)
● Experience with high-level programming languages and big data tools and ecosystems
● In-depth working knowledge of cloud infrastructure such as AWS or Google Cloud
● Experience in integrating with internal and external complex systems that are able to scale and demonstrate security, reliability, scalability, and cost efficiency
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