Sr. AI Engineer

Job Title: Senior AI Engineer

Location: Bengaluru, India – (Hybrid)

About Reltio

At Reltio®, we believe data should fuel business success. Reltio’s AI-powered data unification and management capabilities—encompassing entity resolution, multi-domain master data management (MDM), and data products—transform siloed data from disparate sources into unified, trusted, and interoperable data.

Reltio Data Cloud™ delivers interoperable data where and when it's needed, empowering data and analytics leaders with unparalleled business responsiveness. Leading enterprise brands across multiple industries around the globe rely on our award-winning data unification and cloud-native MDM capabilities to improve efficiency, manage risk, and drive growth.

At Reltio, our values guide everything we do. With an unyielding commitment to prioritizing our “Customer First”, we strive to ensure their success. We embrace our differences and are “Better Together” as One Reltio. We “Simplify and Share” our knowledge to remove obstacles for each other. We “Own It”, holding ourselves accountable for our actions and outcomes. Every day, we innovate and evolve so that today is “Always Better Than Yesterday.”

If you share and embody these values, we invite you to join our team at Reltio and contribute to our mission of excellence.

Reltio has earned numerous awards and top rankings for our technology, our culture, and our people. Founded on a distributed workforce, Reltio offers flexible work arrangements to help our people manage their personal and professional lives. If you’re ready to work on unrivaled technology as part of a collaborative team on a mission to enable digital transformation with connected data, let’s talk!

Job Summary

As a Senior AI Engineer at Reltio, you will be a core part of the team responsible for building intelligent systems that enhance data quality, automate decision-making, and drive entity resolution at scale.

You will work with cross-functional teams to design and deploy advanced AI/ML solutions that are production-ready, scalable, and embedded into our flagship data platform.

This is a high-impact engineering role with exposure to cutting-edge problems in entity resolution, deduplication, identity stitching, record linking, and metadata enrichment.

Job Duties and Responsibilities

• Design, implement, and optimize state-of-the-art AI/ML models for solving real-world data management challenges such as entity resolution, classification, similarity matching, and anomaly detection.
• Work with structured, semi-structured, and unstructured data to extract signals and engineer intelligent features for large-scale ML pipelines.
• Develop scalable ML workflows using Spark, MLlib, PyTorch, TensorFlow, or MLFlow, with seamless integration into production systems.
• Translate business needs into technical design and collaborate with data scientists, product managers, and platform engineers to operationalize models.
• Continuously monitor and improve model performance using feedback loops, A/B testing, drift detection, and retraining strategies.
• Conduct deep dives into customer data challenges and apply innovative machine learning algorithms to address accuracy, speed, and bias.
• Actively contribute to research and experimentation efforts, staying updated with the latest AI trends in graph learning, NLP, probabilistic modeling, etc.
• Document designs and present outcomes to both technical and non-technical stakeholders, fostering transparency and knowledge sharing.

Skills You Must Have

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, or related field. PhD is a plus.
• 4+ years of hands-on experience in developing and deploying machine learning models in production environments.
• Proficiency in Python (NumPy, scikit-learn, pandas, PyTorch/TensorFlow) and experience with large-scale data processing tools (Spark, Kafka, Airflow).
• Strong understanding of ML fundamentals, including classification, clustering, feature selection, hyperparameter tuning, and evaluation metrics.
• Demonstrated experience working with entity resolution, identity graphs, or data deduplication.
• Familiarity with containerized environments (Docker, Kubernetes) and cloud platforms (AWS, GCP, Azure).
• Strong debugging, analytical, and communication skills with a focus on delivery and impact.
• Attention to detail, ability to work independently, and a passion for staying updated with the latest advancements in the field of data science.

Skills Good to Have

• Experience with knowledge graphs, graph-based ML, or embedding techniques.
• Exposure to deep learning applications in data quality, record matching, or information retrieval.
• Experience building explainable AI solutions in regulated domains.
• Prior work in SaaS, B2B enterprise platforms, or data infrastructure companies.