Machine Learning/Data Scientist

Job Title: Machine Learning Data Scientist

Location: Berkeley Heights, NJ (Onsite)

Duration: Contract

Job Description:

We are seeking a talented and motivated Machine Learning Ops Engineer to join our team. As a key member of our Data & Analytics organization, you will play a crucial role in building and supporting a scalable, highly available, and robust Machine Learning (ML) /Deep Learning (DL) platform. This platform will leverage ML/DL frameworks, High-Performance Computing (HPC) machines, and Data Science tools both in the cloud (Azure preferred) and on-premises.

In this dynamic role, you will be exposed to cutting-edge technologies related to ML/DL. The ideal candidate is someone who is driven, focused, and enthusiastic about learning new technologies and implementing them effectively.

Responsibilities:

• Build, install, configure, manage, and scale a state-of-the-art machine learning platform in the cloud (Azure preferred) and on-premises, supporting our Data & Analytics products and solutions.
• Collaborate with data scientists, architects, DevOps engineers, and vendors to implement scalable ML/DL solutions in the cloud and on-premises, addressing complex problems.
• Create and maintain ML/DL pipelines and overall workflow orchestration, covering data collection, preparation, transformation, analysis, experimentation, training, validation, serving, monitoring, etc.
• Implement ML/DL solutions that address performance, scalability, and governance/traceability of machine learning models.
• Stay updated on the latest technologies, products, frameworks, and engage in R&D on information related to ML/DL frameworks, tools, and services.

Qualifications:

• 4+ years of experience delivering DevOps and MLOps in a Production/Enterprise setting.
• Bachelor's degree required; Masters preferred in Computer Science or Data Science.
• Excellent written and oral communication and presentation skills.
• Technical role experience involving platform and infrastructure operation.
• System administration experience of Unix or Linux systems.
• Container-based deployment experience using Docker and Kubernetes.
• Proficiency with the machine learning modeling lifecycle, addressing both functional and technical aspects of model delivery.
• Experience with managing deployment of large distributed systems like Spark, DASK, and H20, and heterogeneous platform components.
• Proficiency in programming languages like Python or R, and understanding statistical foundations of commonly used ML algorithms.
• Experience with Machine Learning frameworks such as Sci-kit, Keras, Theano, TensorFlow, SparkMlib, etc.
• Preferred hands-on experience with IBM Watson Machine Learning systems or related.
• Preferred hands-on experience with HPC Nvidia, CUDA.
• Preferred experience with configuration management tools like Ansible, Puppet.
• Preferred experience in monitoring and performance analysis of Machine Learning platforms using tools like Grafana and Zabbix.

Qualifications & Experience:

• Bachelor's Degree in a related field is required.