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