Design and implement machine learning, information extraction, probabilistic matching algorithms and models
Research and develop innovative, scalable and dynamic solutions to hard problems
Work closely with Machine Learning Scientists (PhDs), ML engineers, data scientists and data engineers to address challenges head on
Use the latest advances in NLP, data science and machine leaning to enhance our products and create new experiences
Scale machine learning algorithm that powers our platform to support our growing customer base and increasing data volume
Be a valued contributor in shaping the future of our products and services
You will be part of our Data Science & Algorithms team and collaborate product management and other team members
Be part of a fast pace, fun focused, agile team
Job Requirement:
4+ years of industry experience
PhD/MS/B.Tech in computer science, information systems, or similar technical field
Strong mathematics, statistics, and data analytics
Solid coding and engineering skills preferably in Machine Learning (not mandatory)
Proficient in Java, Python, and Scala
Industry experience building and productionizing end-to-end systems
Knowledge of Information Extraction, NLP algorithms coupled with Deep Learning
Experience with data processing and storage frameworks like Hadoop, Spark, Kafka etc.
Work Experience
Position Summary
We’re looking for a Machine Learning Engineer to join our team of Phenom. We are expecting below points to full fill this role.
Capable of building accurate machine learning models is main goal of a machine learning engineer
Linear Algebra, Applied Statistics and Probability
Building Data Models
Strong knowledge on NLP
Good understanding of multithreaded and object-oriented software development
Mathematics, Mathematics and Mathematics
Collaborate with Data Engineers to prepare data models required for machine learning models
Collaborate with other product team members to apply state-of-the art Ai methods that include dialogue systems, natural language processing, information retrieval and recommendation systems
Build large scale software systems and numerical computation topics
Use predictive analytics and data mining to solve complex problems and drive business decisions
Should be able to design the accurate ML end-to-end architecture including the data flows, algorithm scalability, and applicability
Tackle situations where Problem is unknown and Solution is unknown
Solve analytical problems, and effectively communicate methodologies and results to the customers
Adept at translating business needs into technical requirements and translating data into actionable insights
Work closely with internal stakeholders such as business teams, product managers, engineering teams, and customer success teams.