Senior AI/ML Project Leader

4 days ago

Hubli, Karnataka, India beBeeTechnical Full time

Key Roles and Responsibilities

We are seeking a skilled AI/ML project leader to oversee the end-to-end design and delivery of an innovative solution —combining NLP, anomaly detection, GenAI/RAG, and rule engines on Cloud platform. The successful candidate will own architecture, technical roadmap, and production reliability while guiding a cross-functional team (ML, Data Eng, Backend, DevOps, QA).

Key responsibilities include:

  • Defining reference architecture (ingestion → lakehouse → features/vectors → models → APIs/UX); making build/buy decisions.
  • Selecting, training, and operationalizing NLP, anomaly/fraud models, and GenAI/RAG components; establishing human-in-the-loop.
  • Implementing experiment tracking, model registry, CI/CD for models, automated evaluation, drift monitoring, rollback.
  • Designing retrieval pipelines (chunking, embeddings, vector namespaces), guardrails (prompt policies, allow-lists, PII redaction), and citation-based responses.
  • Overseeing feature store, labelling strategy, and high-quality gold datasets; enforcing DQ rules and lineage.
  • Right-sizing SKUs; caching/batching; cost/per-token dashboards; SLOs for latency/throughput.
  • Breaking down epics/stories, estimating and sequencing work, unblocking the team, running technical design reviews.
  • Translating business policy into rule + ML ensembles, presenting options, risks, and trade-offs.
  • Establishing testing pyramid (unit, data, model evals, e2e), performance targets, observability dashboards.
  • Producing design docs, runbooks, SOPs; mentoring engineers; uplifting coding and review standards.

Requirements and Qualifications

The ideal candidate will have:

  • At least 10 years of software development experience, with at least 5 years leading AI/ML projects.
  • Hands-on experience in supervised/unsupervised modelling, anomaly detection, NLP (extraction, classification, NER), OCR pipelines; evaluation design (precision/recall, ROC/PR).
  • Familiarity with LangChain/LangGraph; embeddings; vector databases / Azure Cognitive Search (vector); prompt engineering & safety patterns.
  • Experience with MLflow, model registry, online/offline evals, data/version management; CI/CD for models.
  • Knowledge of Delta Lake/Lakehouse (bronze/silver/gold), Azure Data Lake Gen2, Databricks/ADF, schema/versioning, Great Expectations/Deequ.
  • Proficiency in Python (FastAPI), eventing (Event Grid/Service Bus), containerization (AKS/Azure Container Apps), APIM.
  • Familiarity with Cognitive Search, Azure OpenAI, Key Vault, Monitor/App Insights, Purview, Cosmos DB/Azure SQL.
  • Excellent technical decision-making, cross-team coordination, stakeholder communication, and mentoring skills.

Preferred qualifications include certifications in AI/ML disciplines, hands-on experience with explainable AI and AI governance, and familiarity with regulatory compliance standards for financial data (e.g., SOX, GDPR).

Education: Bachelor's Degree in Computer Science or related science field or equivalent.

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