A technology consulting firm operating in the IT Services & Data Science consulting sector, delivering enterprise-grade AI, ML, and analytics solutions to clients across finance, retail, and enterprise verticals. We build production ML systems that drive business outcomes, with a strong focus on model reliability, scalability, and MLOps best practices.
Role:
Senior Machine Learning Engineer (on-site, India) — responsible for designing, building, and productionizing ML systems for high-impact customer engagements.
Role & Responsibilities
- Design and implement end-to-end ML solutions: data ingestion, feature engineering, model development, validation, and deployment to production.
- Productionize models with robust MLOps practices: containerization, CI/CD pipelines, model versioning, automated testing, and deployment orchestration.
- Build scalable inference services and APIs using container orchestration and scalable compute to meet latency and throughput SLAs.
- Collaborate with data engineers, product managers, and stakeholders to translate business requirements into measurable ML deliverables and deployment roadmaps.
- Implement monitoring, alerting, and model observability (performance, drift detection, and explainability) to ensure continuous model health in production.
- Drive code quality through reviews, mentoring junior engineers, and documenting reproducible experiments and engineering playbooks.
Skills & Qualifications
Must-Have
- Python
- PyTorch
- TensorFlow
- Scikit-learn
- Docker
- Kubernetes
Preferred
- AWS SageMaker
- MLflow
- Apache Spark
Benefits & Culture Highlights
- On-site role with direct client engagement and high-visibility projects across industries.
- Opportunities for technical leadership, mentorship, and contribution to engineering best practices and IP.
- Competitive compensation, learning budget for advanced ML tooling, and fast career progression for high performers.
Location: On-site (India). Candidates should be prepared for client-facing work, hands-on implementation, and delivering production-ready ML assets end-to-end.
Skills: machine learning,tensorflow,python,docker,scikit-learn,pytorch,kubernetes
