AI Engineer

JITO

Gurugram District

On-site

INR 1,000,000 - 1,800,000

Full time

14 days+

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Job summary

JITO is looking for a Data Scientist in Gurugram with 5-8 years of experience in Data Science and Machine Learning. The role involves building and deploying ML models, collaborating in cross-functional teams, and working with cloud platforms like AWS.

The ideal candidate should possess a degree in Computer Science or related fields, and familiarity with tools such as Amazon SageMaker, Docker, and TensorFlow.

Qualifications

  • 5–8 years of professional experience in Data Science or Machine Learning.
  • Hands-on experience building, training, and deploying ML models.
  • Understanding of data preprocessing and feature engineering.

Responsibilities

  • Implement AI concepts and frameworks such as autonomous agents.
  • Work with cloud platforms like AWS for machine learning.
  • Collaborate effectively in cross-functional teams.

Skills

Machine Learning
Data Science
Python
Amazon SageMaker
Statistical Analysis

Education

Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics

Tools

scikit-learn
TensorFlow
PyTorch
Docker
Kubernetes

Job description

Minfy Technologies • Gurugram • Posted 3 days ago • Updated 3 days ago

Job Type: FullTimePermanent

Location: Gurugram

Work Mode: Onsite

Experience: Management

Travel Requirements:

Skills:

EducationBachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related fieldStrong academic foundation in statistics, probability, and machine learningShapeCore Experience5–8 years of professional experience in Data Science, Machine Learning, or Applied AIHands-on experience building, training, and deploying ML models in production environmentsStrong understanding of data preprocessing, feature engineering, and model evaluationExperience working on end-to-end ML workflows under guidance of senior/principal team membersAbility to translate business and product requirements into data-driven solutionsShapeMachine Learning & MLOpsPractical experience using Amazon SageMaker for:Model training and tuningModel deployment and inferenceExperience with common ML algorithms using scikit-learn, TensorFlow, or PyTorchFamiliarity with MLOps concepts such as:Model versioningExperiment trackingBasic monitoring and retraining workflowsWorking knowledge of Docker and exposure to Kubernetes-based deploymentsExperience collaborating with ML engineers to operationalize modelsShapeGenerative AI & LLMsHands-on experience developing LLM-powered applications using Amazon Bedrock or similar platformsExperience building or contributing to Retrieval-Augmented Generation (RAG) pipelines, including:Document ingestion and chunkingEmbedding generationSimilarity search using vector databasesPractical knowledge of prompt engineering, prompt tuning, and output evaluationUnderstanding of common LLM failure modes such as hallucinations and grounding issuesAbility to evaluate LLM responses for accuracy, relevance, and safetyShape

Responsibilities

Agentic AI (Growing Expertise)Exposure to Agentic AI concepts and frameworks such as AgentCoreExperience implementing:Simple Autonomous agents or workflowsMulti-step reasoning with predefined toolsFamiliarity with tool-calling, agent orchestration, and workflow automationUnderstanding the importance of:GuardrailsHuman-in-the-loop mechanismsLogging and observability for agent behaviorShapeCloud Platform:Working knowledge of key AWS services, including:S3, Lambda, Redshift, IAMShapeProfessional & Collaboration SkillsStrong Python programming skills and experience working with APIsAbility to work effectively in cross-functional teams (product, engineering, analytics)Willingness to learn quickly in a fast-evolving AI landscapeComfortable taking technical guidance and implementing feedbackClear communication of findings, limitations, and model behavior to non-technical stakeholdersShapeNice to HaveInitial exposure to AI governance, compliance, or ethical AI practicesExperience with monitoring LLM outputs and basic evaluation frameworksCertifications in AWS, Machine Learning, or Data SciencePrior experience in enterprise or cloud-native environments

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