Artificial Intelligence Engineer - Pune District - Sattva Human

    Sattva Human
    Sattva Human Pune District

    1 day ago

    ₹900,000 - ₹2,200,000 (INR) per year * Technology / Internet
    Description

    Roles & Responsibilities:

    As an AI Engineer in Data Intelligence Unit, you will help build and operate the core building blocks of Data Representation learning and Context Engineering across the credit Risk, Fraud/FRM, Sales, Collections & Recovery. You will work with senior engineers and Data scientists to converts raw structured and unstructured data into reliable features, embeddings, retrieval-ready knowledge assets, and repeatable evaluation pipelines – so downstream AI pods can ship models faster, safer, and with measurable quality.

    1) Data Representation Pipelines

    · Prepare and validate datasets from multiple sources (transactions, bureau, device/digital, documents,

    CRM/operations)

    · Implement features engineering pipelines (aggregations, ratios, behavior signals) and maintain feature

    definitions.

    · Build large-scale ML systems: distributed training pipelines, feature stores, model registry, CI/CD for ML, and

    scalable batch + near-real-time scoring services.

    · Support embedding workflows (text/customer/device/dealer/geo) including batch refresh, versioning, and

    lineage.

    2) Knowledge Engineering Support (Canonical Objects & Metadata Assets)

    · Help create/maintain canonical objects, entity dictionaries, taxonomies/ontologies, and labeling guidelines.

    · Support annotation/labeling workflows (quality checks, consistency, sampling) for training and evaluation.

    3) Experimentation & Model Operations

    · Execute training/inference jobs using established frameworks, log experiments and outcomes.

    · Perform error analysis, data leakage checks, and basic model monitoring (drift signals, data anomalies)

    · Contribute to deployment readiness: tests, reproducible configs, and incident triage support.

    4) Retrieval & Context Engineering Support (LLM/RAG enablement)

    · Assist document processing: chunking, cleaning, metadata tagging, indexing access filters.

    · Maintain prompt/context templates, grounding rules, and evaluation sets for RAG/LLM assistants used by

    Pods.

    · Run offline evaluations (retrieval quality, answer quality, regressions) and track metrics across releases.

    5) Engineering Hygiene & Governance

    · Write clean, testable code; follow Git workflows and CI checks.

    · Maintain documentation: dataset cards, feature notes, pipeline SOPs, and release checklists.

    · Follow security/privacy controls for regulated data, ensuring traceability and auditability.

    ______________________________________________________________

    Basic Qualifications:

    · Bachelor's/Master's in CS/Math/Engineering

    · 3 to 5 years' experience in Data Science /Applied ML/ ML Engineering with proven leadership delivering

    production – grade ML system at scale.

    ______________________________________________________________

    Required Skills & Competencies Core (must-have)

    · Programming: Python (strong), SQL (strong); Git; basic unit testing.

    · Data: Pandas/PySpark basics, joins/aggregations/window functions, data validation and profiling.

    · ML Fundamentals: supervised/unsupervised learning, embeddings, train/val/test discipline, metrics, and error analysis.

    · Applied System Mindset: reproducibility, structured debugging, logging/monitoring fundamentals.

    If interested, please share your resume at &

    * This salary range is an estimation made by beBee
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Artificial intelligence engineer