Senior Software Engineer

2 weeks ago

Ajit, India Whatjobs IN C2 Full time

Immediate Joiner required Our AI Core group is pioneering platforms and solutions for Generative AI from AI Agents, RAG, and Knowledge Bases to Data Mining, Anomaly Detection, and LLM fine-tuning. These innovations power flagship products while enabling entirely new offerings. Together, we’re driving a fundamental shift in how businesses manage networks—building intelligent, high-performance multi-agent systems that perceive, learn, and act in real time. At Veltris, innovation isn’t just encouraged—it’s expected. Advance with us and help shape the future of network intelligence. Job Responsibilities · Serve as a thought leader and forward thinker—driving innovative vision across products and platforms, designing and launching strategic ML solutions, and delivering business-wide innovation · Lead the full software development lifecycle (design, testing, deployment, and operations), guide technical discussions and strategy, and actively participate in design reviews, code reviews, and implementation · Develop high-performance, production-ready ML code for next-generation real-time ML platforms, and extend existing ML libraries and frameworks · Collaborate closely with engineers and scientists to accelerate model development, validation, and experimentation cycles, and integrate models and algorithms into production systems at scale Requirements · Degree in Computer Science, Mathematics, or a related field · 8+ years of full SDLC experience (design, coding, reviews, testing, deployment, operations) · 5+ years of experience building and deploying end-to-end ML solutions or platforms in production · Hands-on experience developing Generative AI solutions (RAG, AI Agents, LLM fine-tuning) in production · Experience with large-scale distributed systems on cloud platforms (AWS, Azure, GCP) · Strong ability to solve complex, ambiguous problems Preferred Qualifications · MS/PhD in Computer Science, Machine Learning, or a related discipline · Experience with Graph ML and Graph technologies (e.G., GNNs, GraphRAG) · Experience with distributed Big Data technologies (e.G., Spark, Flink, Kafka, PySpark, Lakehouse, Druid, Hudi, Glue)

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