Senior Machine Learning Engineer

Job Title : Senior Machine Learning Engineer (Generative AI, Machine Learning)

Job Mode : Remote

Overview :

- Are you passionate about innovating with Generative AI and building intelligent systems that redefine whats possible? Do you thrive in solving complex, real-world problems using advanced Machine Learning techniques? If youre excited by the opportunity to create global-scale impact through cutting-edge AI, then this role is for you.

- This is a greenfield opportunity to shape the next generation of AI-driven experiences across Generative AI, Machine Learning, Graph Intelligence, Big Data, and Cloud Computing. You will influence product vision, architect key systems, and drive innovation end to endfrom ideation to production deployment.

Our AI Core Group is pioneering enterprise-grade AI platforms and solutions, spanning :

- AI Agents & Agentic Workflows

- Retrieval-Augmented Generation (RAG)

- Knowledge Graphs & Graph ML

- Anomaly Detection & Predictive Analytics

- LLM Fine-Tuning & Model Optimization

- Multi-Agent Systems for real-time decision-making

These technologies power flagship products and enable new intelligent offerings across the organization. You will help build high-performance, scalable, multi-agent AI systems that learn, reason, and act in real time.

Key Responsibilities :

Strategic Leadership & Innovation :

- Serve as a thought leader and visionary for Generative AI and ML initiatives across products and platforms.

- Drive long-term ML strategy, architecture, and innovationtranslating business needs into scalable AI solutions.

- Identify new opportunities to apply Graph ML, Agentic AI, and multi-agent systems.

Technical Ownership & Execution :

- Lead the full software development lifecycle (SDLC) including design, prototyping, testing, deployment, monitoring, and continuous optimization.

- Conduct and participate in design reviews, code reviews, technical deep-dives, and architectural discussions.

- Develop high-performance, production-grade ML and AI agent code, optimizing for scalability, low latency, and reliability.

Machine Learning & Generative AI Development :

- Build end-to-end ML pipelines, from data ingestion to model deployment and monitoring.

- Architect and deliver Generative AI solutions including RAG pipelines, AI Agents, LLM fine-tuning, and multi-agent orchestration.

- Implement and optimize Graph ML models (e.g., GNNs, GraphRAG) for large-scale knowledge graphs and graph-based intelligence.

Collaboration & Ecosystem Building :

- Partner closely with ML researchers, data engineers, and platform teams to accelerate experimentation and model development.

- Integrate ML models and algorithms into high-throughput distributed systems running on cloud infrastructure.

- Contribute to internal ML frameworks, libraries, tooling, and reusable components.

Required Qualifications :

- Bachelors degree in Computer Science, Mathematics, or related technical field.

- 8+ years of full SDLC experience spanning design, development, testing, deployment, and operations.

- 5+ years of hands-on experience designing, developing, and deploying end-to-end ML systems in production.

- Proven experience building Generative AI solutions, including :

1. RAG pipelines

2. AI Agents / Agentic workflows

3. LLM fine-tuning & optimization

- Mandatory : Deep expertise in Graph Machine Learning (Graph ML) and Agentic AI.

- Strong experience building large-scale, distributed systems on AWS, Azure, or GCP.

- Demonstrated ability to solve complex, ambiguous problems with analytical rigor and innovative thinking.

Preferred Qualifications :

- MS or PhD in Computer Science, Machine Learning, or related discipline.

- Hands-on experience with Graph technologies such as GNNs, GraphRAG, Neo4j, DGL, PyTorch Geometric, or related frameworks.

- Experience with Big Data and distributed compute technologies, including :

1. Apache Spark, Flink, Kafka

2. PySpark

3. Lakehouse architectures

4. Druid, Apache Hudi, AWS Glue

- Familiarity with real-time ML systems, high-throughput data pipelines, and ML observability frameworks.

- Contributions to AI/ML open-source libraries or research publications are a plus.

What We Offer :

- Opportunity to work on groundbreaking Generative AI and Graph ML projects with real-world global impact.

- Highly collaborative environment with senior experts in ML, Distributed Systems, and Advanced AI.

- Ability to influence architecture, product direction, and ML strategy.

- Competitive compensation, benefits, and career advancement opportunities.