Senior Software Engineer (Graph Machine Learning)
New
Based in IndiaFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 8+ years of professional software engineering experience; 5+ years of hands-on experience designing, building, and deploying production machine learning solutions.
- Required Skills
- Cloud ComputingMachine LearningSoftware EngineeringGenerative AIDistributed Systems
Requirements
- Bachelor's degree in Computer Science, Mathematics, Engineering, or a related technical discipline.
- 8+ years of professional software engineering experience with end-to-end SDLC ownership.
- At least 5 years of hands-on experience designing, building, and deploying production machine learning solutions or platforms.
- Strong practical experience with Generative AI technologies, including Retrieval-Augmented Generation (RAG), AI Agents, and LLM fine-tuning.
- Experience building and operating distributed systems on cloud platforms such as AWS, Azure, or Google Cloud Platform.
- Solid programming skills with the ability to develop high-performance, production-ready software.
- Strong analytical thinking and the ability to solve complex technical problems in ambiguous environments.
- Excellent collaboration and communication skills with experience working across multidisciplinary engineering teams.
Responsibilities
- Lead the design, development, testing, deployment, and maintenance of production-grade machine learning solutions across the full software development lifecycle.
- Design and implement scalable Graph Machine Learning and Generative AI solutions that support intelligent, high-performance applications.
- Develop efficient, reliable, and maintainable ML code while enhancing existing machine learning libraries, frameworks, and engineering practices.
- Collaborate closely with software engineers, data scientists, and cross-functional teams to accelerate model development, validation, and deployment.
- Drive technical discussions, participate in architecture reviews and code reviews, and contribute to engineering best practices across the organization.
- Integrate machine learning models into large-scale cloud-based production systems while ensuring scalability, reliability, and operational excellence.
- Research and evaluate emerging AI technologies to continuously improve platform capabilities and product innovation.
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