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)