Senior Director — AI/ML

About Us:Mobileum is a leading provider of Telecom analytics solutions for roaming, core network, security, risk management, domestic and international connectivity testing, and customer intelligence. More than 1,000 customers rely on its Active Intelligence platform, which provides advanced analytics solutions, allowing customers to connect deep network and operational intelligence with real-time actions that increase revenue, improve customer experience, and reduce costs. Know our story: https://www.mobileum.com/Headquartered in Silicon Valley, Mobileum has global offices in Australia, Dubai, Germany, Greece, India, Portugal, Singapore and UK with global HC of over 1800+.Join Mobileum TeamAt Mobileum we recognize that our team is the main reason for our success. What does work with us mean? OpportunitiesRole: Senior Director — AI/ML & GenAIAbout the Job:We are building a high‑impact engineering team to deliver AI/ML and Generative AI capabilities for telecom‑grade platforms (roaming, security, analytics, customer experience). The Sr. Director will lead engineering strategy, architecture, and delivery for GenAI services and platform components. This role blends hands‑on technical depth with strategic leadership across model training, serving, evaluation, infrastructure, and security—customized for the demands of telecom data and performance.Roles & Responsibility: -Engineering Strategy & Technical Vision- Roadmap: Define the engineering roadmap for GenAI platform capabilities—training pipelines, inference layers, and domain‑specific services. - Goals: Establish clear non‑functional goals (e.g., SLOs, quality metrics, performance KPIs) and drive alignment across engineering and product.GenAI Model Lifecycle Management- LLM Workflows: Oversee pretraining, fine‑tuning (SFT), LoRA/PEFT adaptation, and deployment of domain‑specific LLMs. - Guardrails: Build safety filters, hallucination checks, and prompt validation to ensure GenAI output quality and reliability.AI Infrastructure & MLOps- Pipelines: Lead model CI/CD, reproducible pipelines, deployment frameworks, and GPU capacity planning. - Reliability: Partner with SREs to establish observability standards and incident‑handling protocols for AI/LLM systems.Platform & Data Architecture- Services: Architect scalable services supporting vector search, retrieval‑augmented generation (RAG), embedding storage, and model evaluation. - Telco Data: Lead ingestion and integration strategies for telecom‑centric data (CDRs, logs, network KPIs).Release Management & Quality Assurance- Validation: Own model validation strategy—unit/perf tests, dataset quality checks, drift detection, and safety evaluations. - QE Partnership: Collaborate with QE for automation and pre‑release validations.Privacy, Compliance & Responsible AI- Controls: Enforce data minimization, encryption, access controls, and alignment with GDPR/DPDP via engineering practices. - Responsible AI: Guide auditability and transparency in the platform architecture.Team Building & Technical Leadership- Hiring: Recruit and develop AI/ML engineers, MLOps specialists, and platform architects. - Culture: Foster performance engineering, clean architecture, and collaboration.Cross‑functional Execution- Partnerships: Interface with Product, Security, Platform, and QE teams to ensure scalable, reliable GenAI delivery. - Ownership: Maintain architectural and code‑level ownership while influencing cross‑org execution.Desired Profile: -- Telecom domain exposure (xDRs, OSS/BSS, network analytics, firewall/security). - Experience with streaming/OLAP systems (Kafka, ClickHouse) and vector DBs (pgvector, FAISS). - Strong grasp of model evaluation, prompt testing, and inference efficiency techniques.Technical skills:- AI Systems Architecture: End‑to‑end design of scalable, performant GenAI systems. - Operational Readiness: SLO compliance, uptime, monitoring, and incident response. - Hands‑on Technical Leadership: Deep reviews, mentoring, and a high quality bar. - Execution Focus: Outcome ownership and iterative delivery of engineering plans. - Strategic Vision: Prioritize investments and platform evolution roadmap.Tech Stack Overview- LLM/GenAI: PyTorch, HuggingFace, Transformers, LoRA/PEFT - Serving: vLLM, Triton, KServe, REST/gRPC - Data: Kafka, ClickHouse, pgvector, Spark/Flink - MLOps: MLflow, GitHub Actions, Argo, Helm - Infra & Security: Kubernetes, OpenShift, Prometheus, etc.Work Experience:12+ years in software/AI engineering; 5+ years leading ML/GenAI engineering teams.Educational Qualification:Master’s/Ph.D. in CS/EE/Math (or related discipline) with strong grounding in ML, GenAI, and distributed systems.Location: Bangalore