About the job :

We are seeking a highly skilled Senior Machine Learning Engineer to design, develop, and deploy cutting-edge ML and deep learning solutions powering consumer-focused applications.

The role involves building high-impact models for use cases such as predictive safety, content personalization, search optimization, virtual assistants, and time series forecasting.

Core Responsibilities :

- Architect, develop, and implement ML/DL models to solve complex business problems across domains like multilingual text classification, language modeling, and multi-modal learning.

- Design and execute robust evaluation frameworks including A/B testing and performance metrics for both offline and online model assessment.

- Process and analyze large-scale structured and unstructured data using modern big data and streaming technologies to derive actionable insights.

- Write clean, efficient, and reusable code using Python, Scala, or Java, following best practices.

- Collaborate closely with cross-functional teams-including data scientists, software engineers, product managers, and business stakeholders-to align model development with business needs.

- Lead the architecture, development, and delivery of scalable machine learning services that support real-time consumer interactions.

Leadership Responsibilities :

- Guide and mentor a high-performing engineering team, fostering a culture of innovation, collaboration, and engineering excellence.

- Define technical strategy and roadmap in alignment with business goals.

- Drive engineering best practices, process improvements, and operational excellence using Agile/Scrum methodologies.

Required Qualifications :

- Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, Data Science, or a related field.

- 5+ years of hands-on experience designing and deploying ML/DL solutions in a production environment.

- Expertise in Python for ML development (e., scikit-learn, TensorFlow, PyTorch, Hugging Face Transformers).

- Proficiency with big data tools and platforms (e., Spark, Hadoop, Kafka, Airflow).

- Strong understanding of ML concepts including supervised/unsupervised learning, deep learning, NLP, and model interpretability.

- Experience in writing and optimizing SQL queries for data analysis.

- Demonstrated ability to apply statistical thinking and data-driven decision-making.

- Familiarity with software engineering best practices including version control (Git), testing, and CI/CD pipelines.

Preferred (Good to Have) :