ML Engineer

About Company:

We are a global consulting and technology services firm focused on digital transformation. Brillio develops and deploys disruptive solutions which help our clients compete more effectively and capture business value faster. We bring an end-to-end service model to meet the digital transformation needs of our customers. We are a global organization with more than 4,000 employees, headquartered in Edison, NJ with more than 16 offices across the globe serving more than 350 global clients, a significant number of whom are on the Fortune-500. Brillio specializes in leveraging emerging technologies like analytics, security, cloud, mobile, and machine learning.

Job Role: ML Engineer

Responsibilities:

• Model Development: Develop machine learning models and algorithms to solve business problems, leveraging techniques such as supervised learning, unsupervised learning, and deep learning.
• Deployment and Integration: Deploy machine learning models into production environments and integrate them with existing systems and workflows.
• Performance Optimization: Optimize machine learning models for scalability, efficiency, and performance, considering factors such as latency, throughput, and resource utilization.
• Monitoring and Maintenance: Monitor model performance in production, identify and diagnose issues, and implement solutions to ensure continued reliability and effectiveness.
• Collaboration: Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to understand business requirements and deliver solutions that meet stakeholders' needs.
• Research and Innovation: Stay up-to-date with the latest advancements in artificial intelligence and machine learning research, and explore new techniques and methodologies to improve model performance and capabilities.

ML Scientist:

• Data Scientist with ML exp
• Development and maintenance of ML pipeline
• ML Engineer focusing on experimentation and tracking
• Experience and hands on working with simulation techniques
• Strong understanding of ensemble algorithms, especially XGBoost, Random Forest
• Should have understanding on Hyperparameter tuning like Random Search and Grid Search.
• SQL Querying: Intermediate to advanced skills, including window functions, self-joins, and complex joins.
• Statistical Analysis: Proficiency in hypothesis testing (e.g., T-Test, P-Value) and determining statistical significance.
• Python Programming: understanding of Python for data manipulation and analysis.
• MLOPS experience
• Drift Frame Work : Framework for detecting drift
  Automatically monitor track accuracy and trigger model retraining and notifications to restore previous accuracy levels.

Locations: Pune, Chennai, Gurgaon, Hyderabad, Bangalore