Senior Technical Architect Data Science
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Job Location:
Monthly Salary:
Posted on:
30+ days ago
Vacancies:
1 Vacancy
Job Summary
Senior Technical Architect Data Science & Agentic AI
About us
We turn customer challenges into growth opportunities.
Material is a global strategy partner to the worlds most recognizable brands and innovative companies. Our people around the globe thrive by helping organizations design and deliver rewarding customer experiences.
Srijan a Material company is a renowned global digital engineering firm with a reputation for solving complex technology problems using their deep technology expertise and leveraging strategic partnerships with top-tier technology partners.
Role summary
Were seeking a hands-on Sr. Data Science Architect who can lead the end-to-end modeling lifecyclefrom problem framing and experiment design to production deployment and monitoringwhile setting up the technical architecture for ML/GenAI and agentic systems. This is not a data-engineering-heavy role; youll partner with DE/Platform teams but your center of gravity is modeling excellence MLOps and AI solution architecture that moves business KPIs.
What youll do
Strategy & Architecture (Data Sciencefirst)
Own the technical vision for data-science initiatives; translate ambiguous business goals into modellable problems KPIs and NFRs/SLOs.
Define reference architectures for classical ML deep learning and agentic GenAI (RAG tool-use human-in-the-loop) including model registry evaluation harness safety/guardrails and observability.
Make build vs. buy and model/provider choices (OpenAI/Claude/Gemini vs open-source) including optimization strategies (INT8/4 AWQ/GPTQ batching caching).
DS Leadership & Experimentation
Lead problem decomposition feature strategy experiment design (A/B interleaving offline/online eval) error analysis and model iteration.
Guide teams across NLP CV speech time series recommendation clustering/segmentation and causal/uplift where relevant.
Establish rigorous quality bars: data & label quality checks leakage prevention reproducibility and statistical validity.
Productionization & MLOps
Architect CI/CD for models (unit/contract tests drift checks performance gates) model registry/versioning and safe rollouts (shadow canary blue-green).
Design monitoring for accuracy drift data integrity latency cost and safety (toxicity bias hallucination); close the loop with automated retraining triggers where appropriate.
Orchestrate RAG pipelines (chunking embeddings retrieval policies) agent planning/execution and feedback loops for continuous improvement.
Stakeholders & Enablement
Partner with product strategy/innovation design and operations to align roadmaps; run architecture and model review sessions with clear trade-offs.
Provide technical mentorship to data scientists/ML engineers; codify patterns via playbooks ADRs and reference repos.
Collaborate with Ops/SRE to ensure solutions are operable: runbooks SLIs/SLOs on-call and cost controls.
Governance Risk & Compliance
Embed model governance: approvals lineage audit trails PII handling policy-as-code; support GDPR/ISO/SOC2 requirements.
Champion human oversight for agentic systems with clear escalation and decision rights.
Must-have qualifications
1420 years delivering AI/ML in production with 5 years in an architect/tech-lead capacity.
Expert Python and ML stack (PyTorch and/or TensorFlow) plus strong SQL and software engineering fundamentals (testing packaging profiling).
Proven record architecting scalable DS solutions on AWS/Azure/GCP; hands-on with Docker and Kubernetes(collaborating with platform teams rather than building infra from scratch).
MLOps proficiency: MLflow/Kubeflow model registry pipelines (Airflow/Prefect/Vertex/Bedrock/SageMaker pipelines) feature stores and real-time/batch serving (KServe/Seldon/Triton/vLLM/Ray Serve).
Depth across traditional ML and DL (NLP CV speech time-series recommendation clustering/segmentation) and the ability to select/prioritize the right approach for the KPI.
Excellence in communication and stakeholder leadership; experience guiding cross-functional teams (DS MLE DE Product Ops) to ship value.
Preferred qualifications
Agentic AI & RAG: LangChain/LangGraph or equivalent orchestration; vector DBs (pgvector Pinecone Weaviate Qdrant); retrieval policy design and evaluation.
Evaluation & Safety: offline metrics (precision/recall ROC/PR BERT-F1 BLEU/ROUGE) LLM eval harnesses red-teaming prompt/response guardrails.
Experimentation: online testing at scale counterfactual/causal inference telemetry design.
Performance & Cost: quantization speculative decoding KV caching batching/collation throughput tuning on CPU/GPU.
Familiarity with data-viz/decision support (Tableau/Power BI/D3) and UX/HCI collaboration for human-in-the-loop designs.
Consulting experience or multi-vendor delivery; pre-sales/SoW exposure.
Required Experience:
Senior IC
Key Skills
- APIs
- SOAP
- Software Architecture
- .NET
- Design Patterns
- Enterprise Software
- AWS
- Solution Architecture
- Cloud Architecture
- Java
- SSO
- Oracle
