M L Engineer

Mandatory Skills

Data Science , Machine Learning , Artificial Intelligence , Statistics , Deep Learning

Technology name : Machine Learning , Statistics , Deep Learning , ML Ops , Data Analytics

Covering : NLP Linear Regression Classification & Clustering Transfer Learning NLP Forecasting based Models & Algorithms Large Language Models Machine learning frameworks such as Tensorflow, PyTorch, MLlib etc. Data Bricks Sub-technology name: Python, SQL, Spark, Kubernetes, Jenkins, Prometheus

[Job Overview]:

We are looking for an experienced AI/ML Engineer, who can execute projects end to end and take then to production pipeline.

The candidate is expected to lead the AI/ML work across multiple projects, working along with other Data Scientists, ensuring clear understanding and translation of requirements for the team and proposing optimized solutions.

He / She would also need to work on Ad hoc timebound POCs.

Capability building and team upskill would also be expected from him / her. We would want him / her to share the knowledge with other team members and bring them up to the same level , which includes conducting learning sessions across teams and monitoring the progress of the team members.

[Primary Skills]:

• Design and develop various machine learning and deep learning models and systems for high impact consumer applications ranging from predictive safety, content personalizations, search, virtual assistant, time series forecasting and more.
• Work with a broad spectrum of state-of-the-art machine learning and deep learning technologies, in the areas of various machine learning problems such as multilingual text classification, language modelling and multi-modal learning.
• Create metrics and configure A/B testing to evaluate model performance offline and online to inform and convey our impacts to diverse groups of stakeholders.
• Analyse and produce insights from a large amount of dynamic structured and unstructured data using modern big data and streaming technologies
• Produce reusable code according to standard methodologies in Python, Scala or Java
• Collaborate with cross-functional teams of technical members and non-technical members in architecture, design, and code reviews.