Expert Machine Learning Engineer, Data and Analytics
- Bangalore, Karnataka
- Permanent
- Full-time
- Define and drive the ML strategy across business domains, identifying high-impact opportunities for automation, optimization, and prediction.
- Architect scalable ML systems and reusable frameworks that support real-time inference, batch processing, and continuous learning.
- Lead the evaluation and adoption of cutting-edge ML techniques (e.g., foundation models, causal inference, reinforcement learning) to solve complex business problems.
- End-to-End ML Lifecycle Ownership
- Lead the design, development, and deployment of advanced supervised and unsupervised models for use cases such as churn prediction, demand forecasting, fraud detection, and dynamic pricing.
- Own the full ML lifecycle: from problem framing and data exploration to model training, validation, deployment, and monitoring.
- Champion best practices in experimentation, reproducibility, and responsible AI.
- Cross-Functional Leadership & Business Impact
- Partner with senior stakeholders across Sales, Customer Service, Finance, Supply Chain, and Fulfillment to define and prioritize ML initiatives aligned with strategic goals.
- Translate ambiguous business challenges into well-scoped ML solutions with measurable ROI.
- Serve as a technical advisor to executive leadership on AI/ML trends, risks, and opportunities.
- MLOps, Governance & Infrastructure
- Lead the design and implementation of robust MLOps pipelines using tools like DataRobot
- Ensure scalable, secure, and compliant deployment of models in cloud-native environments (AWS, Azure, GCP).
- Establish governance frameworks for model versioning, monitoring, retraining, and auditability.
- Data Engineering & Feature Platform Design
- Collaborate with data engineering teams to define and evolve enterprise-wide feature stores, data contracts, and real-time data pipelines.
- Drive innovation in feature engineering, leveraging domain knowledge and advanced statistical techniques.
- Mentorship, Collaboration & Thought Leadership
- Mentor junior ML engineers and data scientists, fostering a culture of technical excellence and continuous learning.
- Contribute to internal knowledge sharing, technical design reviews, and ML community engagement.
- Publish whitepapers, present at conferences, or lead internal workshops on emerging ML technologies.
- 8-10 years of experience in machine learning product management, AI engineering, or applied data science, with a strong foundation in software engineering.
- Proven experience deploying and scaling ML models in production environments using modern MLOps practices.
- Deep understanding of cloud ML platform capabilities (DataRobot is preferred)
- Strong communication skills with the ability to influence technical and non-technical stakeholders.
- Experience leading ML initiatives in enterprise domains such as Finance, Sales, or Supply Chain.
- Familiarity with advanced ML techniques (e.g., transformers, graph neural networks, time series forecasting, causal modeling).
- Exposure to enterprise platforms such as Salesforce, Oracle.
- Graduate degree (MS or PhD) in Computer Science, Machine Learning, Statistics, or a related field.