Senior Machine Learning Engineer

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

This is a Sr. Machine Learning Engineer role within the Big Data Analytics team to develop and operationalize AI/Machine Learning models. The candidate will work on existing applications and frameworks for data delivery and will also be responsible for developing new models and frameworks, and delivering on business use cases. The role is within a technology group, but involves engagement with business and understanding of operating environments.

Responsibilities:

• Design, develop, and implement machine learning software to analyze large amounts of structured and unstructured data.
• Develop and run machine learning tests and experiments
• Liaising with partner teams and distributed groups to secure rapid engagement, support and problem solving as needed
• Analysis and documentation of data from variety of sources and formats
• Developing mappings and code for integration of data sets from disparate domains
• Quality assurance and testing of analytical routines and data frameworks
• Effective problem solving and issue identification in the event of outages and failures
• Remain up to date on industry research and new techniques in machine learning
• Understanding technology industry trends, how they impact our future solutions and provide strategic direction for the development community.

Qualifications & Competencies:

• Strong background in Algorithms, Data Structures, Machine Learning, Deep Learning and Natural Language Processing.
• Experience must include text analytics such as Named Entity Recognition (NER), Topic Modelling, Sentiment Classification etc.,
• Extensive hand-coding expertise in programming language such as Python and Core Java
• Experience in building and managing REST APIs.
• Experience in systems integration, web services, batch processing
• Experience with distributed systems such as Hadoop/MapReduce, Spark, streaming data processing, cloud architecture.
• Familiarity with machine learning frameworks and libraries (like scikit-learn, SparkML, tensorflow, pytorch etc.,)
• Experience of visualisation tools such as Qlikview, Tableau, MicroStrategy
• Candidate should have strong analytical and numeric capability, a background in analytics and knowledge of analytical tools / data science tools and techniques.
• Candidate should be a strong communicator and a disciplined worker, who is capable of self-motivation and effective problem-solving
• PhD, Masters in computer science, applied mathematics or/computational discipline.