Lead ML Engineer
Machinify- Full Time
- Senior (5 to 8 years), Mid-level (3 to 4 years)
Candidates should possess a Bachelor's degree in Computer Science or an equivalent degree, along with 6+ years of software experience and a strong understanding of machine learning frameworks and models. Experience leading multiple projects leveraging LLMs, GenAI, and Prompt Engineering is required, as is exposure to real-world MLOps deploying models into production. Familiarity with working in a cloud environment and knowledge of LLMs, GenAI, Prompt Engineering, and Copilot are also necessary.
The Machine Learning Engineer is expected to fully own the services built with the ML Scientists, encompassing scalability, availability, metrics, alarms, and latency. They will be responsible for data quality checks, onboarding data to the cloud for modeling, and performing prompt engineering, evaluation, and data analysis. The role involves end-to-end AI solution architecture, LLM inference optimization, control plane design, data plate development, and platform engineering. Furthermore, the ML Engineer will head the ML engineering for a pod, serving as a technical leader for all ML/AI Engineering issues within a delivery pod, and demonstrating comfort in Python and Java.
Global measurement and data analytics provider
Nielsen provides measurement and data analytics services to help businesses understand consumers and markets globally. The company operates through two main divisions: Nielsen Global Media, which offers reliable metrics for the media and advertising industries, and Nielsen Global Connect, which supplies consumer packaged goods manufacturers and retailers with actionable insights about the marketplace. Nielsen combines its proprietary data with other sources to give clients a comprehensive view of current trends and future opportunities. With a presence in over 100 countries, Nielsen aims to support companies in making informed decisions to drive innovation and growth.